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1
Baird, Duncan L. (Duncan Lea). "Dynamically estimating mobile range camera pose from invariant feature measurements." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=26372.
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Complex robotic tasks such as autonomous exploration and grasping demand the co-operation of sensors and actuators. In order to integrate sensor measurements and actuator control schemes we must determine the rigid body transformations that relate the native co-ordinate frames of these devices. Equivalently, we need to estimate the relative pose of sensors and actuators in the systems.We examine the problem of determining the pose of a robot-mounted range-finding camera, and present a class of solutions motivated by the idea that mobile camera calibration is best addressed by an ongoing dynamic estimation process. We use range measurements and known robot kinematics to provide the estimate of camera pose which is maximally consistent with the available data. Our scheme uses scene features that are often present in typical workcell scenes and that are easily and reliably extracted. We develop several formulations of the principles, and present experimental results for both simulated and real data sets.
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Henkel, Hartmuth. "Range-based parameter estimation in diffusion models." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2010. http://dx.doi.org/10.18452/16213.
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Wir studieren das Verhalten des Maximums, des Minimums und des Endwerts zeithomogener eindimensionaler Diffusionen auf endlichen Zeitintervallen. Zuerst beweisen wir mit Hilfe des Malliavin-Kalküls ein Existenzresultat für die gemeinsamen Dichten. Außerdem leiten wir Entwicklungen der gemeinsamen Momente des Tripels (H,L,X) zur Zeit Delta bzgl. Delta her. Dabei steht X für die zugrundeliegende Diffusion, und H und L bezeichnen ihr fortlaufendes Maximum bzw. Minimum. Ein erster Ansatz, der vollständig auf den elementaren Abschätzungen der Doob’schen und der Cauchy-Schwarz’schen Ungleichung beruht, liefert eine Entwicklung bis zur Ordnung 2 bzgl. der Wurzel der Zeitvariablen Delta. Ein komplexerer Ansatz benutzt Partielle-Differentialgleichungstechniken, um eine Entwicklung der einseitigen Austrittswahrscheinlichkeit für gepinnte Diffusionen zu bestimmen. Da eine Entwicklung der Übergangsdichten von Diffusionen bekannt ist, erhält man eine vollständige Entwicklung der gemeinsamen Wahrscheinlichkeit von (H,X) bzgl. Delta. Die entwickelten Verteilungseigenschaften erlauben es uns, eine Theorie für Martingalschätzfunktionen, die aus wertebereich-basierten Daten konstruiert werden, in einem parameterisierten Diffusionsmodell, herzuleiten. Ein Small-Delta-Optimalitätsansatz, der die approximierten Momente benutzt, liefert eine Vereinfachung der vergleichsweise komplizierten Schätzprozedur und wir erhalten asymptotische Optimalitätsresultate für gegen 0 gehende Sampling-Frequenz. Beim Schätzen des Drift-Koeffizienten ist der wertebereich-basierte Ansatz der Methode, die auf equidistanten Beobachtungen der Diffusion beruht, nicht überlegen. Der Effizienzgewinn im Fall des Schätzens des Diffusionskoeffizienten ist hingegen enorm. Die Maxima und Minima in die Analyse miteinzubeziehen senkt die Varianz des Schätzers für den Parameter in diesem Szenario erheblich.We study the behavior of the maximum, the minimum and the terminal value of time-homogeneous one-dimensional diffusions on finite time intervals. To begin with, we prove an existence result for the joint density by means of Malliavin calculus. Moreover, we derive expansions for the joint moments of the triplet (H,L,X) at time Delta w.r.t. Delta. Here, X stands for the underlying diffusion whereas H and L denote its running maximum and its running minimum, respectively. In a first approach that entirely relies on elementary estimates, such as Doob’s inequality and Cauchy-Schwarz’ inequality, we derive an expansion w.r.t. the square root of the time parameter Delta including powers of 2. A more sophisticated ansatz uses partial differential equation techniques to determine an expansion of the one-barrier hitting time probability for pinned diffusions. For an expansion of the transition density of diffusions is known, one obtains an overall expansion of the joint probability of (H,X) w.r.t. Delta. The developed distributional properties enable us to establish a theory for martingale estimating functions constructed from range-based data in a parameterized diffusion model. A small-Delta-optimality approach, that uses the approximated moments, yields a simplification of the relatively complicated estimating procedure and we obtain asymptotic optimality results when the sampling frequency Delta tends to 0. When it comes to estimating the drift coefficient the range-based method is not superior to the method relying on equidistant observations of the underlying diffusion alone. However, there is an enormous gain in efficiency at the estimation for the diffusion coefficient. Incorporating the maximum and the minimum into the analysis significantly lowers the asymptotic variance of the estimators for the parameter in this scenario.
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Karanci, Huseyin. "A Comparative Study Of Regression Analysis, Neural Networks And Case." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612514/index.pdf.
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Construction cost estimating is essential for all of the stakeholders of a construction project from the beginning stage to the end. At early stages of a construction project, the design information and scope definition are very limited, henceduring conceptual (early) cost estimation, achieving high accuracy is very difficult. The level of uncertainty included in the cost estimations should be emphasized for making correct decisions throughout the dynamic stages of construction project management process, especially during early stages. By using range estimating, the level of uncertainties can be identified in cost estimations. This study represents integrations of parametric and probabilistic cost estimation techniques in a comparative base. Combinations of regression analysis, neural networks, case &ndash
based reasoning and bootstrap method are proposed for the conceptual (early) range cost estimations of mass housing projects. Practical methods for early range cost estimation of mass housing projects are provided for construction project management professionals. The methods are applied using bid offers of a Turkish contractor given for 41 mass housing projects. The owner of all projects is Housing Development Administration of Turkey (TOKI). The mass housing projects of TOKI are generally a mix of apartment blocks, social, health and educational facilities, and some projects may also have mosques. Results of the three different approaches are compared for predictive accuracy and predictive variability, and suggestions for early range cost estimation of construction projects are made.
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Vivero, Oskar. "Estimation of long-range dependence." Thesis, University of Manchester, 2010. https://www.research.manchester.ac.uk/portal/en/theses/estimation-of-longrange-dependence(65565876-4ec6-44b3-8181-51b13dca309c).html.
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A set of observations from a random process which exhibit correlations that decay slower than an exponential rate is regarded as long-range dependent. This phenomenon has stimulated great interest in the scientific community as it appears in a wide range of areas of knowledge. For example, this property has been observed in data pertaining to electronics, econometrics, hydrology and biomedical signals.There exist several estimation methods for finding model parameters that help explain the set of observations exhibiting long-range dependence. Among these methods, maximum likelihood is attractive, given its desirable statistical properties such as asymptotic consistency and efficiency. However, its computational complexity makes the implementation of maximum likelihood prohibitive.This thesis presents a group of computationally efficient estimators based on the maximum likelihood framework. The thesis consists of two main parts. The first part is devoted to developing a computationally efficient alternative to the maximum likelihood estimate. This alternative is based on the circulant embedding concept and it is shown to maintain the desirable statistical properties of maximum likelihood.Interesting results are obtained by analysing the circulant embedding estimate. In particular, this thesis shows that the maximum likelihood based methods are ill-conditioned; the estimators' performance will deteriorate significantly when the set of observations is corrupted by errors. The second part of this thesis focuses on developing computationally efficient estimators with improved performance under the presence of errors in the observations.
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Alleyne, Jason C. "Position estimation from range only measurements." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA386399.
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Thesis (M.S. in Mechanical Engineering) Naval Postgraduate School, September 2000.Thesis advisor(s): Healey, Anthony J. "September 2000." Includes bibliographical references (p. 89). Also available online.
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Whaley, Dewey Lonzo. "The Interquartile Range: Theory and Estimation." Digital Commons @ East Tennessee State University, 2005. https://dc.etsu.edu/etd/1030.
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The interquartile range (IQR) is used to describe the spread of a distribution. In an introductory statistics course, the IQR might be introduced as simply the “range within which the middle half of the data points lie.” In other words, it is the distance between the two quartiles, IQR = Q3 - Q1. We will compute the population IQR, the expected value, and the variance of the sample IQR for various continuous distributions. In addition, a bootstrap confidence interval for the population IQR will be evaluated.
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Gal, Avner. "Passive range estimation using over sea multipath." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/23344.
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This thesis suggests an unconventional, unique method for passive range and height estimation of a cruising missile, or other microwave transmitter. Based on multipath propagation, the method uses 5 receiving antennas in a ladder configuration. Ratios of received signal powers are compared with values from lookup tables to determine the correct location of the transmitter. Computer simulation results are presented, to verify the suggested method. (rh)
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Nygaard, John Charles. "Estimation of range error in bistatic sonar." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/30970.
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This thesis examines the range error propagation and uncertainties associated with bistatic sonar operations. An equation for determining range to the target from the receiver is explored for feasibility of practical applications. This particular equation does not require the separation distance between the source and receiver however, it does require an assumption of the mean sound speed over the two paths of the signal even though it could change drastically over a few miles. This thesis explores the contribution of eccentricity on the bistatic ellipse and the associated error. Examples demonstrate these effects by comparing cases of unequal mean sound speeds over the different paths at different values of eccentricity.
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Chuang, Ping Derg. "Range estimation by cepstral techniques in image processing." Thesis, Imperial College London, 1986. http://hdl.handle.net/10044/1/37973.
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Sand, Peter (Peter M. ). 1977. "Long-range video motion estimation using point trajectories." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/38319.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (leaves 97-104).
This thesis describes a new approach to video motion estimation, in which motion is represented using a set of particles. Each particle is an image point sample with a long-duration trajectory and other properties. To optimize these particles, we measure point-based matching along the particle trajectories and distortion between the particles. The resulting motion representation is useful for a variety of applications and differs from optical flow, feature tracking, and parametric or layer-based models. We demonstrate the algorithm on challenging real-world videos that include complex scene geometry, multiple types of occlusion, regions with low texture, and non-rigid deformation.
by Peter Sand.
Ph.D.
11
van, de Beek C. Z., H. Leijnse, P. Hazenberg, and R. Uijlenhoet. "Close-range radar rainfall estimation and error analysis." COPERNICUS GESELLSCHAFT MBH, 2016. http://hdl.handle.net/10150/621508.
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Quantitative precipitation estimation (QPE) using ground-based weather radar is affected by many sources of error. The most important of these are (1) radar calibration, (2) ground clutter, (3) wet-radome attenuation, (4) rain-induced attenuation, (5) vertical variability in rain drop size distribution (DSD), (6) non-uniform beam filling and (7) variations in DSD. This study presents an attempt to separate and quantify these sources of error in flat terrain very close to the radar (1–2 km), where (4), (5) and (6) only play a minor role. Other important errors exist, like beam blockage, WLAN interferences and hail contamination and are briefly mentioned, but not considered in the analysis. A 3-day rainfall event (25–27 August 2010) that produced more than 50 mm of precipitation in De Bilt, the Netherlands, is analyzed using radar, rain gauge and disdrometer data. Without any correction, it is found that the radar severely underestimates the total rain amount (by more than 50 %). The calibration of the radar receiver is operationally monitored by analyzing the received power from the sun. This turns out to cause a 1 dB underestimation. The operational clutter filter applied by KNMI is found to incorrectly identify precipitation as clutter, especially at near-zero Doppler velocities. An alternative simple clutter removal scheme using a clear sky clutter map improves the rainfall estimation slightly. To investigate the effect of wet-radome attenuation, stable returns from buildings close to the radar are analyzed. It is shown that this may have caused an underestimation of up to 4 dB. Finally, a disdrometer is used to derive event and intra-event specific Z–R relations due to variations in the observed DSDs. Such variations may result in errors when applying the operational Marshall–Palmer Z–R relation.
Correcting for all of these effects has a large positive impact on the radar-derived precipitation estimates and yields a good match between radar QPE and gauge measurements, with a difference of 5–8 %. This shows the potential of radar as a tool for rainfall estimation, especially at close ranges, but also underlines the importance of applying radar correction methods as individual errors can have a large detrimental impact on the QPE performance of the radar.
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Simard, Louis. "Hierarchical pose estimation from range data for space applications." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=79261.
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An emerging application for computer vision systems is satellite servicing, involving pose estimation and tracking. Trackers are available but they often require initialization, considerably reducing autonomy. This thesis presents a new hierarchical pose estimation technique based on view-based analysis. The method can handle very sparse range data, is computationally efficient, is robust to noise, and can handle virtually any type of range data. It partitions the problem into two halves, one dealing with estimation of the translation and the other with the orientation. This greatly reduces the complexity of the overall problem without compromising the accuracy of the solution. The resulting algorithm is able to determine pose to within a prescribed accuracy, and from any vantage point within the sensor field of view, at minimal computational complexity for large variations in image noise. Results showing the performance of the system on a prototype space vision system are presented.
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Godfrey, Mark. "Reconciliation and estimation for a short range quantum cryptography system." Thesis, University of Bristol, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.654561.
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The University of Bristol has been developing a free-space, low cost, test-bed quantum cryptography system for the past five years, and the work in this thesis is 'concerned with the algorithms and protocols used in this system. The use scenario is that a hand-held, Alice, device can be used in conjunction with a fixed terminal, Bob, to expand an existing store of shared secret key bits between the two parties. This requires that both devices are compact and low-cost, but with the hand-held Alice device being more so, as there will be a high of ratio of these to Bob devices. To both satisfy the cost constraint and allow rapid prototyping, the physical setup uses off-the-shelf optical and electrical components. The first part· of the work in this thesis analyses the security and performance implications of implementation imperfections. In order to produce a secret key string, novel data processing and reconciliation algorithms are described, optimisation for the scenario where the Alice device has less computational power than that of Bob. Specifically, clock-period recovery, elimination of the background noise by temporal gating, and synchronisation, with low-density parity-check (LDPC) codes being used for the error correction ·stage. In light of recent results on the security of quantum cryptography systems, estimates are calculated that show that the hardware needs to be further improved in order to expand the key store in a convenient period of time. Several improved models are simulated that explore the modifications required to bring the key expansion times into an acceptable range.
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DeCamp, Philip (Philip James). "HeadLock : wide-range head pose estimation for low resolution video." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42411.
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Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, February 2008.Includes bibliographical references (p. 85-87).
This thesis focuses on data mining technologies to extract head pose information from low resolution video recordings. Head pose, as an approximation of gaze direction, is a key indicator of human behavior and interaction. Extracting head pose information from video recordings is a labor intensive endeavor that severely limits the feasibility of using large video corpora to perform tasks that require analysis of human behavior. HeadLock is a novel head pose annotation and tracking tool. Pose annotation is formulated as a semiautomatic process in which a human annotator is aided by computationally generated head pose estimates, significantly reducing the human effort required to accurately annotate video recordings. HeadLock has been designed to perform head pose tracking on video from overhead, wide-angle cameras. The head pose estimation system used by HeadLock can perform pose estimation to arbitrary precision on images that reveal only the top or back of a head. This system takes a 3D model-based approach in which heads are modeled as 3D surfaces covered with localized features. The set of features used can be reliably extracted from both hair and skin regions at any resolution, providing better performance for images that may contain small facial regions and no discernible facial features. HeadLock is evaluated on video recorded for the Human Speechome Project (HSP), a research initiative to study human language development by analyzing longitudinal audio-video recordings of a developing child. Results indicate that HeadLock may enable annotation of head pose at ten times the speed of a manual approach. In addition to head tracking, this thesis describes the data collection and data management systems that have been developed for HSP, providing a comprehensive example of how very large corpora of video recordings may be used to research human development, health and behavior.
by Philip DeCamp.
S.M.
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Smith, Brian M. (Brian Matthew) 1975. "Lower bounds on pose estimation with high range-resolution radar." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86635.
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Morrison, Richard B. "Fiducial marker detection and pose estimation from LIDAR range data." Thesis, Monterey, California : Naval Postgraduate School, 2010. http://edocs.nps.edu/npspubs/scholarly/theses/2010/Mar/10Mar%5FMorrison.pdf.
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Thesis (M.S. in Modeling, Virtual Environments, and Simulation (Moves))--Naval Postgraduate School, March 2010.Thesis Advisor(s): Kolsch, Mathias ; Chung, Timothy H. "March 2010." Author(s) subject terms: LIDAR, point cloud, feature extraction, fiducial marker, pose estimation. Includes bibliographical references (p. 95-99). Also available in print.
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Subramanian, Anbumani. "Image Segmentation and Range Estimation Using a Moving-aperture Lens." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/32289.
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Given 2D images, it still remains a big challenge in the field of
computer vision to group the image points into logical objects
(segmentation) and to determine the locations in the scene (range
estimation). Despite the decades of research, a single solution
is yet to be found. Through our research we have demonstrated
that a possible solution is to use moving aperture lens. This lens
has the effect of introducing small, repeating movements of the
camera center so that objects appear to translate in the image, by
an amount that depends on distance from the plane of focus. Our
novel method employs optical flow techniques to an image sequence,
captured using a video camera with a moving aperture lens. For a
stationary scene, optical flow magnitudes and direction are
directly related to the three-dimensional object distance and
location from the observer. Exploiting this information, we have
successfully extracted objects at different depths and estimated
the locations of objects in the scene, with respect to the plane
of focus. Our work therefore demonstrates an ability for
passive range estimation, without emitting any energy in an
environment. Other potential applications include video
compression, 3D video broadcast, teleconferencing and autonomous
vehicle navigation.Master of Science
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Oguntade, Ayoade O. "Range Estimation for Tactical Radio Waveforms using Link Budget Analysis." University of Toledo / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1271210750.
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Bilgin, Ozan Ozgun. "Short Range Thrusting Projectile Tracking." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614609/index.pdf.
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Short range thrusting projectiles are one of the various threats against armored vehicles and helicopters on the battlefield. Developing a countermeasure for this kind of projectiles is very crucial since they are vast in number and easy to operate on the battlefield. A countermeasure may consist of fire point prediction of the projectile and attack the launcher of it, or it may be the impact point prediction of the projectile and apply a hard-kill counter measure on its way to the ally target. For both of the countermeasure concepts, dynamics and parameters of the projectile must be estimated precisely. In this thesis, dynamic models for thrusting and ballistic flight modes of thrusting projectile are obtained. Three different tracking filters are suggested for precise tracking of the projectiles and their estimation performances are compared. These filters are the Extended Kalman Filter (EKF), the Particle Filter (PF) and the Marginalized Particle Filter (MPF).
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Kim, Y. S., and R. Eng. "Estimation of Tec and Range of EMP Source Using an Improved Ionospheric Correction Model." International Foundation for Telemetering, 1992. http://hdl.handle.net/10150/611957.
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International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, CaliforniaAn improved ionospheric delay correction model for a transionospheric electromagnetic pulse (EMP) is used for estimating the total-electron-content (TEC) profile of the path and accurate ranging of the EMP source. For a known pair of time of arrival (TOA) measurements at two frequency channels, the ionospheric TEC information is estimated using a simple numerical technique. This TEC information is then used for computing ionospheric group delay and pulse broadening effect correction to determine the free space range. The model prediction is compared with the experimental test results. The study results show that the model predictions are in good agreement with the test results.
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Ramalingam, Santhosh. "Empirical evaluvation [sic] of range query size estimation through polynomial approximation /." Available to subscribers only, 2007. http://proquest.umi.com/pqdweb?did=1400971271&sid=7&Fmt=2&clientId=1509&RQT=309&VName=PQD.
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Ahmadzadeh, Amir Masoud. "Capacity and Cell-Range Estimation for Multitraffic Users in Mobile WiMAX." Thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-19122.
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The fundamentals for continued growth of broadband wireless remain sound. According to the Ericsson’s official forecasts, the addressable global market of wireless internet broadband connectivity reaches to 320 million users by the end of 2010. The opportunity for BWA/WiMAX to serve those who want to switch to broadband service is huge in many parts of the world where wireline technologies may not be feasible.The current document (Capacity and Cell-range Estimation for Multitraffic Users in Mobile WiMAX) is prepared as a master’s program final thesis to peruse the service provision capabilities of Mobile WiMAX innovate technology in more details. An elaborate excerpt of the technical subjects of IEEE-802.16e-2005 standard is gathered in the first chapter to provide the reader with a practical concept of Mobile WiMAX technology. The following chapter is aimed to collect the required knowledge for WiMAX planning problem. An innovate methodology to calculate the system’s actual throughput and a traffic model for mixed application users are proposed with a step by step description to derive an algorithm to determine the maximum number of subscribers that each specific Mobile WiMAX sector may support. The report also contains a Matlab code –enclose in the appendix– that tries to implement the entire algorithm for different system parameter and traffic cases to ease the Mobile WiMAX planning problem. The last chapter introduces the mostly used propagation models that suit the WiMAX applications.The presented methodology would help those operators that plan to implement a wide coverage network in a city. Using the introduced methodology, service providers will be able to estimate the number of base stations and hence the network investment and profitability.Uppsatsnivå: D
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Webb, Samuel Robert. "Kinematic GNSS tropospheric estimation and mitigation over a range of altitudes." Thesis, University of Newcastle upon Tyne, 2015. http://hdl.handle.net/10443/2823.
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This thesis investigates the potential for estimating tropospheric delay from Global Navigation Satellite Systems (GNSS) stations on moving platforms experiencing a change in altitude. The ability to accurately estimate tropospheric delay in kinematic GNSS positioning has implications for improved height accuracy due to the mitigation of a major GNSS error source, and for the collection of atmospheric water vapour data for meteorology and climate studies. The potential for extending current kinematic GNSS positioning estimates of tropospheric delay from sea level based studies to airborne experiments, and the achievable height accuracy from a range of tropospheric mitigation strategies used in airborne GNSS positioning, are explored. An experiment was established at the Snowdon Mountain Railway (SMR), utilising the railway to collect a repeatable kinematic dataset, profiling 950 m of the lower atmosphere over a 50 day period. GNSS stations on stable platforms and meteorological sensors were installed at the extremities of the trajectory, allowing reference tropospheric delays and coordinates to be established. The retrieval of zenith wet delay (ZWD) from kinematic GNSS solutions using tropospheric estimation strategies is validated against an interpolated reference ZWD between GNSS stations on stable platforms, together with profiles from 100 m resolution runs of the UK Met Office Unified Model. Agreement between reference ZWD values and a combined GPS+GLONASS precise point positioning (PPP) solution is demonstrated with an accuracy of 11.6 mm (RMS), similar to a relative positioning solution and previous shipborne studies. The impact on the height accuracy from estimating tropospheric delay in kinematic GNSS positioning is examined by comparing absolute and relative GNSS positioning solutions to a reference trajectory generated from a relative GNSS positioning solution ii processed with reference to the GNSS stations on stable platforms situated at the extremities of the SMR. A height accuracy with a standard deviation of 72 mm was demonstrated for the GPS+GLONASS PPP solution, similar to a GPS-only relative solution, and providing an improvement over the GPS-only PPP solution.
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Quinton, Brendon. "The Effect of Home Range Estimation Techniques on Habitat Use Analysis." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6359.
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The term “home range” refers to the area in which an animal spends most of its time during everyday activities. This study examined the effects of four different home range estimation techniques on the proportions of habitats located therein. The study utilized a point dataset collected for twenty individual Florida Black Bears (Ursus americanus floridanus), occurring in five different areas throughout the state of Florida. Each dataset was used to create home ranges using the following techniques: (1) Minimum Convex Polygon, (2) Kernel Density Estimation, (3) Characteristic Hull Polygon, and (4) Time-Geographic Density Estimation, a new home range estimator which has not been thoroughly tested prior to this study. A dataset of land cover types was clipped with each home range and the areas of habitats were recalculated. The proportion of each land cover type was evaluated and the results compared first within each dataset, then between all datasets used. Repeated measures analysis of variance (ANOVA) was used to determine whether the four home range estimation techniques produced significantly different areas and proportions of each habitat type. These results were then evaluated to determine whether the method of home range estimation has an effect on which land cover types are most utilized by a species and, therefore, which habitats are considered preferable. While the choice of home range estimation did not have an effect on which habitats were determined to be most frequently visited, it did affect the amount of each habitat found within each home range. Furthermore, there was a statistically significant change in the amount of developed areas, specifically between the characteristic hull polygon and kernel density estimation methods. These results suggest the choice of home range estimator affects habitat analysis and that researchers should use the method best suited for the dataset.
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Viksten, Fredrik. "Local Features for Range and Vision-Based Robotic Automation." Doctoral thesis, Linköpings universitet, Informationskodning, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-57333.
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Robotic automation has been a part of state-of-the-art manufacturing for many decades. Robotic manipulators are used for such tasks as welding, painting, pick and place tasks etc. Robotic manipulators are quite flexible and adaptable to new tasks, but a typical robot-based production cell requires extensive specification of the robot motion and construction of tools and fixtures for material handling. This incurs a large effort both in time and monetary expenses. The task of a vision system in this setting is to simplify the control and guidance of the robot and to reduce the need for supporting material handling machinery. This dissertation examines performance and properties of the current state-of-the-art local features within the setting of object pose estimation. This is done through an extensive set of experiments replicating various potential problems to which a vision system in a robotic cell could be subjected. The dissertation presents new local features which are shown to increase the performance of object pose estimation. A new local descriptor details how to use log-polar sampled image patches for truly rotational invariant matching. This representation is also extended to use a scale-space interest point detector which in turn makes it very competitive in our experiments. A number of variations of already available descriptors are constructed resulting in new and competitive features, among them a scale-space based Patch-duplet. In this dissertation a successful vision-based object pose estimation system is extended for multi-cue integration, yielding increased robustness and accuracy. Robustness is increased through algorithmic multi-cue integration, combining the individual strengths of multiple local features. Increased accuracy is achieved by utilizing manipulator movement and applying temporal multi-cue integration. This is implemented using a real flexible robotic manipulator arm. Besides work done on local features for ordinary image data a number of local features for range data has also been developed. This dissertation describes the theory behind and the application of the scene tensor to the problem of object pose estimation. The scene tensor is a fourth order tensor representation using projective geometry. It is shown how to use the scene tensor as a detector as well as how to apply it to the task of object pose estimation. The object pose estimation system is extended to work with 3D data. A novel way of handling sampling of range data when constructing a detector is discussed. A volume rasterization method is presented and the classic Harris detector is adapted to it. Finally, a novel region detector, called Maximally Robust Range Regions, is presented. All developed detectors are compared in a detector repeatability test.
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Pallotti, Daniel. "Electric Range Estimation algorithm for a high performance Plug-in Hybrid Electric Vehicle application." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.
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The main purpose of this activity is the creation of a function able to estimate the residual electric range, for a high-performance Plug-In Hybrid Electric Vehicle in electric and hybrid mode. A function that is able to report the same information that a normal on-board computer provides to the driver in real time. The model within which this function was built deals with the management of the strategies for determining the torque required in each situation within the imposed driving cycle, in order to determine the right electric / hybrid split depending on the circumstances.
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Khan, Zarak Ali. "Error Analysis of Angle and Range Estimation in a Range Limited Antenna System Using Music and Modified Root Pisarenko Algorithms." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/46213.
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The Range Limited Antenna (RLA) has the ability to track and pin-point RF devices operating within a certain accepted range. Using two antenna arrays, each made up of several elements, direction-finding algorithms such as MUSIC and Modified Root Pisarenko (MRP) are used to estimate the angles of arrival of incoming signals. Using the estimated angles of arrival, a range estimation algorithm is used to estimate the distance of the emitter from the antenna array.
The aim of this thesis is to check the sensitivity of the range estimation and to form a statistical analysis for such conditions. Conditions of error are introduced into the system and several extensive Monte Carlo simulations are run for both MUSIC and MRP. Upon simulating physical errors in the antenna set-up, it is realized that the range estimation algorithm is sensitive to the slightest of phase shift differences, cable loss differences, mixer mismatches, and antenna mismatches.Master of Science
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Dammes, Timo [Verfasser]. "Probabilistic Range Estimation for Wireless Indoor Localization in NLOS Scenarios / Timo Dammes." Aachen : Shaker, 2015. http://d-nb.info/1069050407/34.
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Quek, Chin Khoon. "Vision based control and target range estimation for small unmanned aerial vehicle." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Dec%5FQuek.pdf.
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Thesis (M.S. in Engineering Science (Mechanical Engineering))--Naval Postgraduate School, December 2005.Thesis Advisor(s): Isaac I. Kaminer. Includes bibliographical references (p.39). Also available online.
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Costa, Yuri Ajala da. "A proposal for full-range fat fraction estimation using magnitude MR imaging." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-01102018-083519/.
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Current methods for estimation of proton density fat fraction (PDFF) of the liver using magnitude magnetic resonance (MR) imaging face the challenge of correctly estimating it when fat is the dominant molecule, i.e. PDFF is more than 50%. Therefore, the accuracy of the methods is limited to half-range operation. We introduce a method based on neural networks for regression capable of estimating over the full range of fat fractions. We built a neural network based on the angles and distances between the data in the discrete MR signal (ADALIFE), using these as features associated to different PDFFs and as input for the network. Tests were performed assessing ADALIFE against dual echo, triple echo, and especially Multi-interference, a state-of-the-art method to estimate PDFFs, with simulated signals at various signal-to-noise (SNR) values. Results were compared in order to verify repeatability and agreement using regression analysis, Bland-Altman and REC curves. Results for Multi-interference were similar to its in-vivo literature, showing the relevance of a simulation. ADALIFE was able to correctly estimate fat fractions up to 100%, breaking the current paradigm for full-range estimation using only off-line post processing. Within half-range, our method outperformed Multi-interference in repeatability and agreement, with narrower limits of agreement and lower expected error at any SNR.Os métodos atuais para estimação de gordura hepática por densidade de prótons (PDFF) utilizando imagem de magnitude de ressonância magnética (RM) enfrentam o desafio de estimar corretamente quando a gordura é a molécula dominante, ou seja, PDFF é maior que 50%. Assim, a acurácia desses métodos é limitada a meio intervalo de operação. Apresentamos aqui um método baseado em redes neurais para regressão capaz de estimar pelo intervalo completo de frações de gordura. Construímos uma rede neural baseada nos ângulos e distâncias entre os dados do sinal discreto da imagem de RM (ADALIFE), usando esses atributos associados a diferentes valores de PDFF, com sinais simulados considerando diferentes relações sinal-ruído (SNR). Resultados foram comparados para verificar a repetibilidade e concordância através de análise de regressão, Bland- Altman e curvas de característica de erro de regressão (REC). Resultados para o método Multi-interferência (estado-da-arte) foram similares aos relatados in vivo pela literatura, ressaltando a relevância das simulações. ADALIFE foi capaz de estimar corretamente frações de gordura até 100%, quebrando o paradigma para intervalo completo de operação utilizando apenas processamento posterior à aquisição de imagens ou sinais. Considerando meio intervalo, nosso método superou o estado-da-arte em termos de repetibilidade e concordância, com limites mais estreitos e menor erro esperado em qualquer SNR.
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Desbouvries, François. "Rangs de déplacement et algorithmes rapides... /." Paris : École nationale supérieure des télécommunications, 1991. http://catalogue.bnf.fr/ark:/12148/cb35452554k.
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FROST, WILLIAM EDWARD. "DEVELOPMENT OF RESOURCE VALUE RATINGS AND ESTIMATION OF CARRYING CAPACITY OF SOUTHERN ARIZONA RANGELANDS." Diss., The University of Arizona, 1986. http://hdl.handle.net/10150/188146.
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The objective of this research was development and testing of a method for estimating cattle carrying capacities. A series of studies were conducted in developing this method. Range site and vegetation production data were grouped by topographic position and multiple linear regression equations were calculated for predicting vegetation production as a site deviated from the average case of a given range site. Overstory-understory relationships from the literature were adapted into overstory canopy cover classes for predicting understory production and tested on a variety of range sites. Use of these classes produced understory biomass estimates within 13% of measured biomass. Range condition class and understory aspect dominance by forage vs. non-forage species were investigated as estimators of forage value of the understory vegetation. Both were significantly related to amount of forage in the understory. However, understory aspect proved to be a better estimator when individual comparisons were examined. The previous findings, along with Soil Conservation Service range site guides, were used to calculate resource value ratings. Adjustment factors to be applied to the resource value ratings were calculated, using data from the literature, to account for the effects of slope and distance from water on forage utilization by cattle. These resource value ratings and adjustment factors form the basis of the carrying capacity estimation method. Pastures identified as properly utilized were used in testing the method developed. Pastures were mapped for range site, vegetation, slope and water location. Maps were converted to digital form and analyzed using the Map Analysis Package (MAP) computer program (Tomlin, 1975). Construction of a final range site-vegetation-slope-distance from water map, assigning of resource value ratings and adjustment factors, and computation of final carrying capacity estimates were accomplished using MAP. Carrying capacity estimates from the developed method were well correlated to estimates from ocular reconnaissance and area allowable use methods, r = .87 and .97, respectively, and with the actual use (perceived proper use), r = .95. These estimates were accomplished without intensive field sampling. The only information required was range site designation, amount of overstory canopy cover, understory aspect class, percent slope and water location.
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Akter, Shirin. "Regional flood estimation method for the Mt. Lofty Ranges /." Title page, abstract and contents only, 1992. http://web4.library.adelaide.edu.au/theses/09ENS/09ensa315.pdf.
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Smith, Lerdudomsak, Mitsuhiro Kadota, Shinji Doki, and Shigeru Okuma. "Harmonic Currents Estimation and Compensation Method for Current Control System of IPMSM in Overmodulation Range." IEEE, 2007. http://hdl.handle.net/2237/9474.
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Trotter, Matthew. "Range finding in passive wireless sensor networks using power-optimized waveforms." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/42916.
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Passive wireless sensor networks (WSNs) are quickly becoming popular for many applications such as article tracking, position location, temperature sensing, and passive data storage. Passive tags and sensors are unique in that they collect their electrical energy by harvesting it from the ambient environment. Tags with charge pumps collect their energy from the signal they receive from the transmitting source. The efficiency of converting the received signal to DC power is greatly enhanced using a power-optimized waveform (POW).
Measurements in the first part of this dissertation show that a POW can provide efficiency gains of up to 12 dB compared to a sine-wave input. Tracking the real-time location of these passive tags is a specialized feature used in some applications such as animal tracking. A passive WSN that uses POWs for the improvement of energy-harvesting may also estimate the range to a tag by measuring the time delay of propagation from the transmitter to the tag and back to the transmitter. The maximum-likelihood (ML) estimator is used for estimating this time delay, which simplifies to taking the cross-correlation of the received signal with the transmitted signal.
This research characterizes key aspects of performing range estimations in passive WSNs using POWs. The shape of the POW has a directly-measurable effect on ranging performance. Measurements and simulations show that the RMS bandwidth of the waveform has an inversely proportional relationship to the uncertainty of a range measurement. The clutter of an environment greatly affects the uncertainty and bias exhibited by a range estimator. Random frequency-selective environments with heavy clutter are shown to produce estimation uncertainties more than 20 dB higher than the theoretical lower bound. Estimation in random frequency-flat environments is well-behaved and fits the theory quite nicely. Nonlinear circuits such as the charge pump distort the POW during reflection, which biases the range estimations. This research derives an empirical model for predicting the estimation bias for Dickson charge pumps and verifies it with simulations and measurements.
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Barr, Michael. "The Influence of the Projected Coordinate System on Animal Home Range Estimation Area." Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/5343.
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Animal home range estimations are important for conservation planning and protecting the habitat of threatened species. The accuracy of home range calculations is influenced by the map projection chosen in a geographic information system (GIS) for data analysis. Different methods of projection will distort spatial data in different ways, so it is important to choose a projection that meets the needs of the research. The large number of projections in use today and the lack of distortion comparison between the various types make selecting the most appropriate projection a difficult decision. The purpose of this study is to quantify and compare the amount of area distortion in animal home range estimations when projected into a number of projected coordinate systems in order to understand how the chosen projection influences analysis. The objectives of this research are accomplished by analyzing the tracking data of four species from different regions in North and South America. The home range of each individual from the four species datasets is calculated using the Characteristic Hull Polygon method for home range estimation and then projected into eight projected coordinate systems of various scales and projection type, including equal area, conformal, equidistant, and compromise projections. A continental Albers Equal Area projection is then used as a baseline area for the calculation of a distortion measurement ratio and magnitude of distortion statistic. The distortion measurement ratio and magnitude calculations provide a measurement of the quantity of area distortion caused by a projection. Results show the amount distortion associated with each type of projection method and how the amount of distortion changes for a projection based on geographic location. These findings show how the choice of map projection can have a large influence on data analysis and illustrate the importance of using an appropriate PCS for the needs of a given study. Distorted perceptions can influence decision-making, so it is important to recognize how a map projection can influence the analysis and interpretation of spatial data.
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Deleskog, Viktor. "Sensor Localization Calibration of Ground Sensor Networks with Acoustic Range Measurements." Thesis, Linköpings universitet, Reglerteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-81655.
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Advances in the development of simple and cheap sensors give new possibilities with large sensor network deployments in monitoring and surveillance applications. Commonly, the sensor positions are not known, specifically, when sensors are randomly spread in a big area. Low cost sensors are constructed with as few components as possible to keep price and energy consumption down. This implies that self-positioning and communication capabilities are low. So the question: “How do you localize such sensors with good precision with a feasible approach?” is central. When no information is available a stable and robust localization algorithm is needed. In this thesis an acoustic sensor network is considered. With a movable acoustic source a well-defined and audible signal is transmitted at different spots. The sensors measure the time of arrival which corresponds to distance. A two-step sensor localization approach is applied that utilizes the estimated distances. A novel approach in the first step is presented to incorporate more measurements and gain more position information. Localization and ranging performance is evaluated with simulations and data collected at field trials. The results show that the novel approach attains higher accuracy and robustness.
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Valdivieso, Serrano Luis Hilmar. "Fractionally integrated processes of Ornstein-Uhlenbeck type." Pontificia Universidad Católica del Perú, 2014. http://repositorio.pucp.edu.pe/index/handle/123456789/97091.
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An estimation methodology to deal with fractionally integrated processes of Ornstein- Uhlenbeck type is proposed. The methodology is based on the continuous Whittle contrast. A simulation study is performed by driving this process with a symmetric CGMY background Lévy process.
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Breloy, Arnaud. "Algorithmes d’estimation et de détection en contexte hétérogène rang faible." Thesis, Université Paris-Saclay (ComUE), 2015. http://www.theses.fr/2015SACLN021/document.
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Une des finalités du traitement d’antenne est la détection et la localisation de cibles en milieu bruité. Dans la plupart des cas pratiques, comme par exemple le RADAR ou le SONAR actif, il faut estimer dans un premier temps les propriétés statistiques du bruit, et plus précisément sa matrice de covariance ; on dispose à cette fin de données secondaires supposées identiquement distribuées. Dans ce contexte, les hypothèses suivantes sont généralement formulées : bruit gaussien, données secondaires ne contenant que du bruit, et bien sûr matériels fonctionnant parfaitement. Il est toutefois connu aujourd’hui que le bruit en RADAR est de nature impulsive et que l’hypothèse Gaussienne est parfois mal adaptée. C’est pourquoi, depuis quelques années, le bruit et en particulier le fouillis de sol est modélisé par des processus elliptiques, et principalement des Spherically Invariant Random Vectors (SIRV). Dans ce nouveau cadre, la Sample Covariance Matrix (SCM) estimant classiquement la matrice de covariance du bruit entraîne des pertes de performances très importantes des détecteurs / estimateurs. Dans ce contexte non-gaussien, d’autres estimateurs de la matrice de covariance mieux adaptés à cette statistique du bruit ont été développés : la Matrice du Point Fixe (MPF) et les M-estimateurs.Parallèlement, dans un cadre où le bruit se décompose sous la forme d’une somme d’un fouillis rang faible et d’un bruit blanc, la matrice de covariance totale est structurée sous la forme rang faible plus identité. Cette information peut être utilisée dans le processus d'estimation afin de réduire le nombre de données nécessaires. De plus, il aussi est possible d'utiliser le projecteur orthogonal au sous espace fouillis à la place de la matrice de covariance ce qui nécessite moins de données secondaires et d’être aussi plus robuste aux données aberrantes. On calcule classiquement ce projecteur à partir d'un estimateur de la matrice de covariance. Néanmoins l'état de l'art ne présente pas d'estimateurs à la fois être robustes aux distributions hétérogènes, et rendant compte de la structure rang faible des données. C'est pourquoi ces travaux se focalisent sur le développement de nouveaux estimateurs (de covariance et de sous espace), directement adaptés au contexte considéré. Les contributions de cette thèse s'orientent donc autour de trois axes :- Nous présenterons tout d'abord un modèle statistique précis : celui de sources hétérogènes ayant une covariance rang faible noyées dans un bruit blanc gaussien. Ce modèle et est, par exemple, fortement justifié pour des applications de type radar. Il à cependant peu été étudié pour la problématique d'estimation de matrice de covariance. Nous dériverons donc l'expression du maximum de vraisemblance de la matrice de covariance pour ce contexte. Cette expression n'étant pas une forme close, nous développerons différents algorithmes pour tenter de l'atteindre efficacement.- Nous développons de nouveaux estimateurs directs de projecteur sur le sous espace fouillis, ne nécessitant pas un estimé de la matrice de covariance intermédiaire, adaptés au contexte considéré.- Nous étudierons les performances des estimateurs proposés et de l'état de l'art sur une application de Space Time Adaptative Processing (STAP) pour radar aéroporté, au travers de simulations et de données réellesOne purpose of array processing is the detection and location of a target in a noisy environment. In most cases (as RADAR or active SONAR), statistical properties of the noise, especially its covariance matrix, have to be estimated using i.i.d. samples. Within this context, several hypotheses are usually made: Gaussian distribution, training data containing only noise, perfect hardware. Nevertheless, it is well known that a Gaussian distribution doesn’t provide a good empirical fit to RADAR clutter data. That’s why noise is now modeled by elliptical process, mainly Spherically Invariant Random Vectors (SIRV). In this new context, the use of the SCM (Sample Covariance Matrix), a classical estimate of the covariance matrix, leads to a loss of performances of detectors/estimators. More efficient estimators have been developed, such as the Fixed Point Estimator and M-estimators.If the noise is modeled as a low-rank clutter plus white Gaussian noise, the total covariance matrix is structured as low rank plus identity. This information can be used in the estimation process to reduce the number of samples required to reach acceptable performance. Moreover, it is possible to estimate the basis vectors of the clutter-plus-noise orthogonal subspace rather than the total covariance matrix of the clutter, which requires less data and is more robust to outliers. The orthogonal projection to the clutter plus noise subspace is usually calculated from an estimatd of the covariance matrix. Nevertheless, the state of art does not provide estimators that are both robust to various distributions and low rank structured.In this Thesis, we therefore develop new estimators that are fitting the considered context, to fill this gap. The contributions are following three axes :- We present a precise statistical model : low rank heterogeneous sources embedded in a white Gaussian noise.We express the maximum likelihood estimator for this context.Since this estimator has no closed form, we develop several algorithms to reach it effitiently.- For the considered context, we develop direct clutter subspace estimators that are not requiring an intermediate Covariance Matrix estimate.- We study the performances of the proposed methods on a Space Time Adaptive Processing for airborne radar application. Tests are performed on both synthetic and real data
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Almeida, Jorge Manuel Soares de. "Active tracking of dynamic multivariate agents using vectorial range data." Doctoral thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/16988.
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Doutoramento em Engenharia MecânicaO objeto principal da presente tese é o estudo de sistemas avançados de segurança, no âmbito da segurança automóvel, baseando-se na previsão de movimentos e ações dos agentes externos. Esta tese propõe tratar os agentes como entidades dinâmicas, com motivações e constrangimentos próprios. Apresenta-se, para tal, novas técnicas de seguimento dos referidos agentes levando em linha de conta as suas especificidades. Em decorrência, estuda-se dedicadamente dois tipos de agentes: os veículos automóveis e os peões. Quanto aos veículos automóveis, propõe-se melhorar a capacidade de previsão de movimentos recorrendo a modelos avançados que representam corretamente os constrangimentos presentes nos veículos. Assim, foram desenvolvidos algoritmos avançados de seguimento de agentes com recurso a modelos de movimento não holonómicos. Estes algoritmos fazem uso de dados vectoriais de distância fornecidos por sensores de distância laser. Para os peões, devido à sua complexidade (designadamente a ausência de constrangimentos de movimentos) propõe-se que a análise da sua linguagem corporal permita detetar atempadamente possíveis intenções de movimentos. Assim, foram desenvolvidos algoritmos de perceção de pose de peões adaptados ao campo da segurança automóvel com recurso a uso de dados de distâncias 3D obtidos com uma câmara stereo. De notar que os diversos algoritmos foram testados em experiências realizadas em ambiente real.
The main topic of this thesis is the study of advanced safety systems, in the field of automotive safety, based on the prediction of the movement and actions of external agents. This thesis proposes to treat the agents as dynamic entities with their own motivations as constraints. As so, new target tracking techniques are proposed taking into account the targets’ specificities. Therefore, two different types of agents are dedicatedly studied: automobile vehicles and pedestrians. For the automobile vehicles, a technique to improve motion prediction by the use of advanced motion models is proposed, these models will correctly represent the constrains that exist in this kind of vehicle. With this goal, advanced target tracking algorithms coupled with nonholonomic motion models were developed. These algorithms make use of vectorial range data supplied by laser range sensors. Concerning the pedestrians, due to the problem complexity (mainly due to the lack of any specific motion constraint), it is proposed that the analysis of the pedestrians body language will allow to detected early the pedestrian intentions and movements. As so, pedestrian pose estimation algorithms specially adapted to the field of automotive safety were developed; these algorithms use 3D point cloud data obtained with a stereo camera. The various algorithms were tested in experiments conducted in real conditions.
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Vorst, Philipp [Verfasser]. "Mapping, Localization, and Trajectory Estimation with Mobile Robots Using Long-Range Passive RFID / Philipp Vorst." München : Verlag Dr. Hut, 2011. http://d-nb.info/1016531311/34.
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Hickey, Kenneth J. "Ocean surface current estimation using a long-range, single-station, high-frequency ground wave radar." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0008/MQ42394.pdf.
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Umasuthan, M. "Recognition and position estimation of 3D objects from range images using algebraic and moment invariants." Thesis, Heriot-Watt University, 1995. http://hdl.handle.net/10399/763.
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Anttonen, A. (Antti). "Estimation of energy detection thresholds and error probability for amplitude-modulated short-range communication radios." Doctoral thesis, Oulun yliopisto, 2011. http://urn.fi/urn:isbn:9789514297052.
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Abstract In this thesis, novel data and channel estimation methods are proposed and analyzed for low-complexity short-range communication (SRC) radios. Low complexity is challenging to achieve especially in very wideband or millimeter-wave SRC radios where phase recovery and energy capture from numerous multipaths easily become a bottleneck for system design. A specific type of transceiver is selected using pulse amplitude modulation (PAM) at the transmitter and energy detection (ED) at the receiver, and it is thus called an ED-PAM system. Nonnegative PAM alphabets allow using an ED structure which enables a phase-unaware detection method for avoiding complicated phase recovery at the receiver. Moreover, the ED-PAM approach results in a simple multipath energy capture, and only one real decision variable, whose dimension is independent of the symbol alphabet size, is needed. In comparison with optimal phase-aware detection, the appealing simplicity of suboptimal ED-PAM systems is achieved at the cost of the need for a higher transmitted signal energy or shorter link distance for obtaining a sufficient signal-to-noise ratio (SNR) at the receiver, as ED-PAM systems are more vulnerable to the effects of noise and interference. On the other hand, the consequences of requiring a higher SNR may not be severe in the type of SRC scenarios where a sufficient received SNR is readily available due to a short link distance. Furthermore, significant interference can be avoided by signal design. However, what has slowed down the development of ED-PAM systems is that efficient symbol decision threshold estimation and related error probability analysis in multipath fading channels have remained as unsolved problems. Based on the above observations, this thesis contributes to the state-of-the-art of the design and analysis for ED-PAM systems as follows. Firstly, a closed-form near-optimal decision threshold selection method, which adapts to a time-varying channel gain and enables an arbitrary choice of the PAM alphabet size and an integer time-bandwidth product of the receiver filters, is proposed. Secondly, two blind estimation schemes of the parameters for the threshold estimation are introduced. Thirdly, analytical error probability evaluation in frequency-selective multipath fading channels is addressed. Special attention is given to lognormal fading channels, which are typically used to model very wideband SRC multipath channels. Finally, analytical error probability evaluation with nonideal parameter estimation is presented. The results can be used in designing low-complexity transceivers for very wideband and millimeter-wave wireless SRC devices of the futureTiivistelmä Tässä työssä esitetään ja analysoidaan uusia data- ja kanavaestimointimenetelmiä, joiden tavoitteena on yksinkertaistaa lähikommunikaatiota (short-range communication, SRC) langattomien laitteiden välillä. SRC-radioiden yksinkertainen toteutus on poikkeuksellisen haasteellista silloin, kun käytetään erittäin suurta kaistanleveyttä tai millimetriaaltoalueen tiedonsiirtoa. Tällöin vastaanottimen yksinkertaisen toteutuksen voivat estää esimerkiksi kantoaallon vaiheen estimointi ja signaalienergian kerääminen lukuisilta kanavan monitiekomponenteilta. Näistä lähtökohdista valitaan SRC-radion järjestelmämalliksi positiiviseen pulssiamplitudimodulaatioon (pulse amplitude modulation, PAM) perustuva lähetin ja energiailmaisimeen (energy detection, ED) perustuva vastaanotin. ED-PAM-järjestelmän ei tarvitse tietää vastaanotetun signaalin vaihetta ja signaalienergian kerääminen tapahtuu yksinkertaisen diversiteettiyhdistelytekniikan avulla. Lisäksi ilmaisuun tarvitaan vain yksi reaalinen päätösmuuttuja, jonka dimensio on riippumaton PAM-tasojen määrästä. ED-PAM-tekniikan yksinkertaisuutta optimaaliseen vaihetietoiseen ilmaisuun verrattuna ei saavuteta ilmaiseksi. Yhtenä rajoituksena on alioptimaalisen ED-PAM-tekniikan luontainen taipumus vahvistaa kohinan ja häiriöiden vaikutusta symbolin päätöksenteossa. Kohinan vahvistus ei välttämättä ole suuri ongelma niissä SRC-radioissa, joissa pienen linkkietäisyyden johdosta riittävä signaali-kohinasuhde vastaanottimessa voidaan kohinan vahvistuksesta huolimatta saavuttaa. Myös häiriöiden vahvistuksen vaikutusta voidaan tehokkaasti vähentää signaalisuunnittelulla. Joka tapauksessa ED-PAM-tekniikan käyttöönottoa on hidastanut tehokkaiden symbolipäätöskynnysten estimointi- ja analysointimenetelmien puuttuminen. Edellä mainitut havainnot ovat motivoineet löytämään uusia suunnittelu- ja analyysimenetelmiä ED-PAM-järjestelmille seuraavasti. Symbolipäätöskynnysten estimointiin johdetaan lähes optimaalinen suljetun muodon menetelmä, joka kykenee adaptoitumaan muuttuvassa kanavassa ja valitsemaan mielivaltaisen kokonaisluvun sekä PAM-tasojen määrälle että vastaanottimen aika-kaistanleveystulolle. Lisäksi esitetään kaksi sokeaa päätöskynnysten estimointimenetelmää, jotka eivät tarvitse redundanttista opetussignaalia. Työn toisessa osassa ED-PAM-järjestelmän symbolivirhesuhdetta analysoidaan taajuusselektiivisessä monitiekanavassa. Analyysissä keskitytään log-normaalijakauman mukaan häipyvään kanavaan. Seuraavaksi analyysia laajennetaan ottamalla mukaan epäideaalisten kynnysarvojen estimoinnin vaikutus. Saavutettuja tuloksia voidaan hyödyntää erittäin laajakaistaisten ja millimetriaaltoalueen SRC-laitteiden suunnittelussa
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Monie, Aubrey. "Factors that influence the estimation of three-dimensional gleno-humeral joint repositioning error in asymptomatic healthy subjects." University of Western Australia. School of Surgery, 2008. http://theses.library.uwa.edu.au/adt-WU2009.0073.
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Joint Position Sense (JPS) of the shoulder as determined by repeated repositioning tasks has been performed under different constrained testing conditions. The variability in the testing protocols for JPS testing of the gleno-humeral joint may incorporate different movement patterns, numbers of trials used to derived a specific JPS variable and range of motion. All of these aspects may play an important role in the assessment of G-H JPS testing. When using a new instrument for assessing JPS all of these issues need to be examined to document the optimal testing protocols for subsequent clinical assessments. By undertaking these studies future clinical trials may be more optimally assessed to determine if there are differences between dominant and non-dominant arms as well as the presence of JPS changes in performance associated with pathology and rehabilitation. This study used a 3-dimensional tracking system to examined gleno-humeral JPS using 2 open kinetic chain movement patterns. The 'conventional' 90 degree abducted, externally rotated movement was compared to the hypothetically more functional D2 movement pattern used in proprioceptive neuromuscular facilitatory techniques. These two patterns were tested at different ranges (low and high). Two cohorts (n=12, n=16) of normal healthy athletic males aged 17-35 years, performed matching tasks of both left and right arms. The second cohort (n=16) were assessed with and without strapping the gleno-humeral joint with sports tape. Accuracy (overall bias) and precision (variability) scores were determined for progressively greater numbers of trials. The findings of the study show that estimates of JPS accuracy and precision become more stable from data derived from 5 to 6 matching trials. There were no statistical differences between sides [95%CI ± 1.5cm]. The accuracy but not precision improved as subjects approximated the 'high' end of range in the 'conventional' or D2 pattern. Furthermore, no systematic differences were detected at different ranges of movement or movement patterns with or without the application of sports tape. These findings provide a guide to the number of trials that optimise the testing of the gleno-humeral joint and also suggest that in normal controls the magnitude of differences between sides and movement patterns is similar. These findings also iii indicate that sports tape applied to the shoulder may not significantly change the JPS performance in healthy, athletic males.
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Thomas, Liya. "Automated Detection of Surface Defects on Barked Hardwood Logs and Stems Using 3-D Laser Scanned Data." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/29038.
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This dissertation presents an automated detection algorithm that identifies severe external defects on the surfaces of barked hardwood logs and stems. The defects detected are at least 0.5 inch in height and at least 3 inches in diameter, which are severe, medium to large in size, and have external surface rises. Hundreds of real log defect samples were measured, photographed, and categorized to summarize the main defect features and to build a defect knowledge base. Three-dimensional laser-scanned range data capture the external log shapes and portray bark pattern, defective knobs, and depressions.
The log data are extremely noisy, have missing data, and include severe outliers induced by loose bark that dangles from the log trunk. Because the circle model is nonlinear and presents both additive and non-additive errors, a new robust generalized M-estimator has been developed that is different from the ones proposed in the statistical literature for linear regression. Circle fitting is performed by standardizing the residuals via scale estimates calculated by means of projection statistics and incorporated in the Huber objective function to bound the influence of the outliers in the estimates. The projection statistics are based on 2-D radial-vector coordinates instead of the row vectors of the Jacobian matrix as proposed in the statistical literature dealing with linear regression. This approach proves effective in that it makes the GM-estimator to be influence bounded and thereby, robust against outliers.
Severe defects are identified through the analysis of 3-D log data using decision rules obtained from analyzing the knowledge base. Contour curves are generated from radial distances, which are determined by robust 2-D circle fitting to the log-data cross sections. The algorithm detected 63 from a total of 68 severe defects. There were 10 non-defective regions falsely identified as defects. When these were calculated as areas, the algorithm locates 97.6% of the defect area, and falsely identifies 1.5% of the total clear area as defective.Ph. D.
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Stancescu, Daniel O. "Bootstrap Methods for the Estimation of the Variance of Partial Sums." University of Cincinnati / OhioLINK, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=ucin998055058.
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Jones, Michael D. "DNA-based Population Estimation, Harvest Vulnerability, and Home Range Dynamics of Black Bears in Western Maryland." Thesis, West Virginia University, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=1522522.
Full textAbstract:
After nearly being extirpated from the state, black bears in Maryland have rebounded to a point where recreational harvest has now become an important management tool. Having a better understanding of bear population parameters, movements, and harvest vulnerability allows managers to implement hunting more effectively and responsibly. To estimate demographics of the Maryland bear population, we implemented noninvasive genetic sampling of bear hair during summer 2011. We used a model-based sampling design that allowed us to collect samples more efficiently. We used presence-only maximum entropy (Maxent) modeling to classify the study area based on predicted probability of bear occurrence, and allocated the majority of our hair snares to areas with high or medium probabilities. Using microsatellite analysis and mark-recapture methods, we estimated the bear population at 701 individuals. This represents a nearly doubling of the population since the previous estimate in 2005. Our density estimate (0.25 bears/km2) is comparable to other estimates from southeastern and mid-Atlantic states. Our sampling approach did lead to more efficient sample collection, with more hair samples collected at snares located in areas with predicted high or medium probability of bear occurrence than those in low probability areas. However, in the eastern portion of our study area, where bear occurrence is presumed to be much lower, our sampling effort seemed insufficient to collect enough samples for reliable abundance estimation. As a first step toward quantifying harvest vulnerability, we used Global Positioning System (GPS) units to record movements and spatial behaviors of 108 bear hunters during the 2005–2007 Maryland bear hunting seasons. Median values showed that hunters traveled 2.9 km per hunting event, but only 0.6 km from their starting point. Hunters did not seem to show any preferential use of areas based on the landscape metrics we examined (e.g., elevation, distance from nearest road) except cover type, where 81% of locations were in deciduous forests. We found few differences between spatial behaviors of groups of hunters based on harvest success, residency, and previous bear hunting experience, as classified using post-hunt mail surveys. One notable difference is that successful hunters used steeper slopes than unsuccessful hunters. We also found that hunter perceptions of total distance traveled and distance from nearest roads were often highly inaccurate, showing that hunter surveys are not a useful tool for collecting those data. For Garrett County, Maryland, we used the hunter locations to create a Maxent model of the spatial distribution of harvest pressure. We also created a model using fall telemetry locations of female bears and compared the models to identify areas of high (i.e., high hunter and high bear occurrence) and low (i.e., low hunter and high bear occurrence) harvest vulnerability. Both models showed higher probability of occurrence on public lands. Both high and low vulnerability areas comprised small portions of the county. The low vulnerability areas included 9 larger blocks (>1 km 2), which were 2.3 times steeper, 2.0 times farther from roads, and 1.5 times farther from streams than the medians for the study area. Those characteristics may limit hunter access to and use of the areas. Our predicted high vulnerability areas did not correspond to most previous bear harvest locations, indicating that our definition of harvest vulnerability often does not translate to actual harvest. Finally, we used GPS collars to track female bear locations in Garrett County and examine home range dynamics. Fixed kernel estimates for annual, spring, summer, and fall home ranges were 10.40 km 2, 8.93 km2, 16.08 km2, and 19.35 km 2, respectively. Fall and summer home ranges were larger than spring home ranges, but summer and fall ranges were similar. Solitary females had mean spring home ranges 6.9 times larger than females with cubs-of-the-year, but ranges did not differ during other seasons. Bears exhibited high levels of home range fidelity, with home range centroids shifting little among seasons or years. Intraspecific overlap of home ranges occurred during all 3 seasons, but was most common in summer. The results of this study provide Maryland bear biologists and managers with essential information about the state’s bear population. Home range estimates represent important baseline information to determine appropriate spatial scales of management. The abundance estimates will be used to set proper harvest quotas with the goal of slowing the bear population growth. The hunter movement analysis and harvest vulnerability modeling may be used by managers to adjust harvest regulations to increase the efficacy of the hunting seasons.
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Rust, Henning. "Detection of long-range dependence : applications in climatology and hydrology." Phd thesis, Universität Potsdam, 2007. http://opus.kobv.de/ubp/volltexte/2007/1334/.
Full textAbstract:
It is desirable to reduce the potential threats that result from the
variability of nature, such as droughts or heat waves that lead to
food shortage, or the other extreme, floods that lead to severe
damage. To prevent such catastrophic events, it is necessary to
understand, and to be capable of characterising, nature's variability.
Typically one aims to describe the underlying dynamics of geophysical
records with differential equations. There are, however, situations
where this does not support the objectives, or is not feasible, e.g.,
when little is known about the system, or it is too complex for the
model parameters to be identified. In such situations it is beneficial
to regard certain influences as random, and describe them with
stochastic processes. In this thesis I focus on such a description
with linear stochastic processes of the FARIMA type and concentrate on
the detection of long-range dependence. Long-range dependent processes
show an algebraic (i.e. slow) decay of the autocorrelation
function. Detection of the latter is important with respect to,
e.g. trend tests and uncertainty analysis.
Aiming to provide a reliable and powerful strategy for the detection
of long-range dependence, I suggest a way of addressing the problem
which is somewhat different from standard approaches. Commonly used
methods are based either on investigating the asymptotic behaviour
(e.g., log-periodogram regression), or on finding a suitable
potentially long-range dependent model (e.g., FARIMA[p,d,q]) and test
the fractional difference parameter d for compatibility with
zero. Here, I suggest to rephrase the problem as a model selection
task, i.e.comparing the most suitable long-range dependent and the
most suitable short-range dependent model. Approaching the task this
way requires a) a suitable class of long-range and short-range
dependent models along with suitable means for parameter estimation
and b) a reliable model selection strategy, capable of discriminating
also non-nested models. With the flexible FARIMA model class together
with the Whittle estimator the first requirement is
fulfilled. Standard model selection strategies, e.g., the
likelihood-ratio test, is for a comparison of non-nested models
frequently not powerful enough. Thus, I suggest to extend this
strategy with a simulation based model selection approach suitable for
such a direct comparison. The approach follows the procedure of
a statistical test, with the likelihood-ratio as the test
statistic. Its distribution is obtained via simulations using the two
models under consideration. For two simple models and different
parameter values, I investigate the reliability of p-value and power
estimates obtained from the simulated distributions. The result turned
out to be dependent on the model parameters. However, in many cases
the estimates allow an adequate model selection to be established.
An important feature of this approach is that it immediately reveals
the ability or inability to discriminate between the two models under
consideration.
Two applications, a trend detection problem in temperature records and
an uncertainty analysis for flood return level estimation, accentuate the
importance of having reliable methods at hand for the detection of
long-range dependence. In the case of trend detection, falsely
concluding long-range dependence implies an underestimation of a trend
and possibly leads to a delay of measures needed to take in order to
counteract the trend. Ignoring long-range dependence, although
present, leads to an underestimation of confidence intervals and thus
to an unjustified belief in safety, as it is the case for the
return level uncertainty analysis. A reliable detection of long-range
dependence is thus highly relevant in practical applications.
Examples related to extreme value analysis are not limited to
hydrological applications. The increased uncertainty of return level
estimates is a potentially problem for all records from autocorrelated
processes, an interesting examples in this respect is the assessment
of the maximum strength of wind gusts, which is important for
designing wind turbines. The detection of long-range dependence is
also a relevant problem in the exploration of financial market
volatility. With rephrasing the detection problem as a model
selection task and suggesting refined methods for model comparison,
this thesis contributes to the discussion on and development of
methods for the detection of long-range dependence.Die potentiellen Gefahren und Auswirkungen der natürlicher Klimavariabilitäten zu reduzieren ist ein wünschenswertes Ziel. Solche Gefahren sind etwa Dürren und Hitzewellen, die zu Wasserknappheit führen oder, das andere Extrem, Überflutungen, die einen erheblichen Schaden an der Infrastruktur nach sich ziehen können. Um solche katastrophalen Ereignisse zu vermeiden, ist es notwendig die Dynamik der Natur zu verstehen und beschreiben zu können. Typischerweise wird versucht die Dynamik geophysikalischer Datenreihen mit Differentialgleichungssystemen zu beschreiben. Es gibt allerdings Situationen in denen dieses Vorgehen nicht zielführend oder technisch nicht möglich ist. Dieses sind Situationen in denen wenig Wissen über das System vorliegt oder es zu komplex ist um die Modellparameter zu identifizieren. Hier ist es sinnvoll einige Einflüsse als zufällig zu betrachten und mit Hilfe stochastischer Prozesse zu modellieren. In dieser Arbeit wird eine solche Beschreibung mit linearen stochastischen Prozessen der FARIMA-Klasse angestrebt. Besonderer Fokus liegt auf der Detektion von langreichweitigen Korrelationen. Langreichweitig korrelierte Prozesse sind solche mit einer algebraisch, d.h. langsam, abfallenden Autokorrelationsfunktion. Eine verläßliche Erkennung dieser Prozesse ist relevant für Trenddetektion und Unsicherheitsanalysen. Um eine verläßliche Strategie für die Detektion langreichweitig korrelierter Prozesse zur Verfügung zu stellen, wird in der Arbeit ein anderer als der Standardweg vorgeschlagen. Gewöhnlich werden Methoden eingesetzt, die das asymptotische Verhalten untersuchen, z.B. Regression im Periodogramm. Oder aber es wird versucht ein passendes potentiell langreichweitig korreliertes Modell zu finden, z.B. aus der FARIMA Klasse, und den geschätzten fraktionalen Differenzierungsparameter d auf Verträglichkeit mit dem trivialen Wert Null zu testen. In der Arbeit wird vorgeschlagen das Problem der Detektion langreichweitiger Korrelationen als Modellselektionsproblem umzuformulieren, d.h. das beste kurzreichweitig und das beste langreichweitig korrelierte Modell zu vergleichen. Diese Herangehensweise erfordert a) eine geeignete Klasse von lang- und kurzreichweitig korrelierten Prozessen und b) eine verläßliche Modellselektionsstrategie, auch für nichtgenestete Modelle. Mit der flexiblen FARIMA-Klasse und dem Whittleschen Ansatz zur Parameterschätzung ist die erste Voraussetzung erfüllt. Hingegen sind standard Ansätze zur Modellselektion, wie z.B. der Likelihood-Ratio-Test, für nichtgenestete Modelle oft nicht trennscharf genug. Es wird daher vorgeschlagen diese Strategie mit einem simulationsbasierten Ansatz zu ergänzen, der insbesondere für die direkte Diskriminierung nichtgenesteter Modelle geeignet ist. Der Ansatz folgt einem statistischen Test mit dem Quotienten der Likelihood als Teststatistik. Ihre Verteilung wird über Simulationen mit den beiden zu unterscheidenden Modellen ermittelt. Für zwei einfache Modelle und verschiedene Parameterwerte wird die Verläßlichkeit der Schätzungen für p-Wert und Power untersucht. Das Ergebnis hängt von den Modellparametern ab. Es konnte jedoch in vielen Fällen eine adäquate Modellselektion etabliert werden. Ein wichtige Eigenschaft dieser Strategie ist, dass unmittelbar offengelegt wird, wie gut sich die betrachteten Modelle unterscheiden lassen. Zwei Anwendungen, die Trenddetektion in Temperaturzeitreihen und die Unsicherheitsanalyse für Bemessungshochwasser, betonen den Bedarf an verläßlichen Methoden für die Detektion langreichweitiger Korrelationen. Im Falle der Trenddetektion führt ein fälschlicherweise gezogener Schluß auf langreichweitige Korrelationen zu einer Unterschätzung eines Trends, was wiederum zu einer möglicherweise verzögerten Einleitung von Maßnahmen führt, die diesem entgegenwirken sollen. Im Fall von Abflußzeitreihen führt die Nichtbeachtung von vorliegenden langreichweitigen Korrelationen zu einer Unterschätzung der Unsicherheit von Bemessungsgrößen. Eine verläßliche Detektion von langreichweitig Korrelierten Prozesse ist somit von hoher Bedeutung in der praktischen Zeitreihenanalyse. Beispiele mit Bezug zu extremem Ereignissen beschränken sich nicht nur auf die Hochwasseranalyse. Eine erhöhte Unsicherheit in der Bestimmung von extremen Ereignissen ist ein potentielles Problem von allen autokorrelierten Prozessen. Ein weiteres interessantes Beispiel ist hier die Abschätzung von maximalen Windstärken in Böen, welche bei der Konstruktion von Windrädern eine Rolle spielt. Mit der Umformulierung des Detektionsproblems als Modellselektionsfrage und mit der Bereitstellung geeigneter Modellselektionsstrategie trägt diese Arbeit zur Diskussion und Entwicklung von Methoden im Bereich der Detektion von langreichweitigen Korrelationen bei.
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Moritz, Malte, and Anton Pettersson. "Estimation of Local Map from Radar Data." Thesis, Linköpings universitet, Reglerteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-111916.
Full textAbstract:
Autonomous features in vehicles is already a big part of the automobile area and now many companies are looking for ways to make vehicles fully autonomous. Autonomous vehicles need to get information about the surrounding environment. The information is extracted from exteroceptive sensors and today vehicles often use laser scanners for this purpose. Laser scanners are very expensive and fragile, it is therefore interesting to investigate if cheaper radar sensors could be used. One big challenge when it comes to autonomous vehicles is to be able to use the exteroceptive sensors and extract a position of the vehicle and at the same time get a map of the environment. The area of Simultaneous Localization and Mapping (SLAM) is a well explored area when using laser scanners but is not that well explored when using radars. It has been investigated if it is possible to use radar sensors on a truck to create a map of the area where the truck drives. The truck has been equipped with ego-motion sensors and radars and the data from them has been fused together to get a position of the truck and to get a map of the surrounding environment, i.e. a SLAM algorithm has been implemented. The map is represented by an Occupancy Grid Map (OGM) which should only consist of static objects. The OGM is updated probabilistically by using a binary Bayes filter. To localize the truck with help of motion sensors an Extended Kalman Filter (EKF) is used together with a map and a scan match method. All these methods are put together to create a SLAM algorithm. A range rate filter method is used to filter out noise and non-static measurements from the radar. The results of this thesis show that it is possible to use radar sensors to create a map of a truck's surroundings. The quality of the map is considered to be good and details such as space between parked trucks, signs and light posts can be distinguished. It has also been proven that methods with low performance on their own can together with other methods work very well in the SLAM algorithm. Overall the SLAM algorithm works well but when driving in unexplored areas with a low number of objects problems with positioning might occur. A real time system has also been implemented and the map can be seen at the same time as the truck is manoeuvred.