Relevant bibliographies by topics / Doppler radar

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Doppler radar'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 July 2024

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Journal articles on the topic "Doppler radar"

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Gong, Jiangkun, Jun Yan, Deren Li, and Deyong Kong. "Detection of Micro-Doppler Signals of Drones Using Radar Systems with Different Radar Dwell Times." Drones 6, no. 9 (September 19, 2022): 262. http://dx.doi.org/10.3390/drones6090262.

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Not any radar dwell time of a drone radar is suitable for detecting micro-Doppler (or jet engine modulation, JEM) produced by the rotating blades in radar signals of drones. Theoretically, any X-band drone radar system should detect micro-Doppler of blades because of the micro-Doppler effect and partial resonance effect. Yet, we analyzed radar data detected by three radar systems with different radar dwell times but similar frequency and velocity resolution, including Radar−α, Radar−β, and Radar−γ with radar dwell times of 2.7 ms, 20 ms, and 89 ms, respectively. The results indicate that Radar−β is the best radar for detecting micro-Doppler (i.e., JEM signals) produced by the rotating blades of a quadrotor drone, DJI Phantom 4, because the detection probability of JEM signals is almost 100%, with approximately 2 peaks, whose magnitudes are similar to that of the body Doppler. In contrast, Radar−α can barely detect any micro-Doppler, and Radar−γ detects weak micro-Doppler signals, whose magnitude is only 10% of the body Doppler’s. Proper radar dwell time is the key to micro-Doppler detection. This research provides an idea for designing a cognitive micro-Doppler radar by changing radar dwell time for detecting and tracking micro-Doppler signals of drones.
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Baranov, G., R. Gabruk, and I. Gorishna. "Features of Usіng Pulse-Doppler Radars for Determіnatіon Low-Altіtude Targets." Metrology and instruments, no. 2 (May 3, 2019): 62–66. http://dx.doi.org/10.33955/2307-2180(2)2019.62-66.

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In this paper, we analyzed the features of Doppler processing in radars. In ground based radars, the amount of clutter in the radar receiver depends heavily on the radar-to-target geometry. The amount clutter is considerably higher when the radar beam has to face toward the ground. Furthermore, radars employing high PRFs have to deal with an increased amount of clutter due to folding in range. Clutter introduces additional difficulties for airborne radars when detecting ground targets and other targets flying at low altitudes. This is illustrated in Fig. 10.5. Returns from ground clutter emanate from ranges equal to the radar altitude to those which exceed the slant range along the main-beam, with considerable clutter returns in the side-lobes and main-beam. The presence of such large amounts of clutter interferes with radar detection capabilities and makes it extremely difficult to detect targets in the look-down mode. This difficulty in detecting ground or low altitude targets has led to the development of pulse Doppler radars where other targets, kinematics such as Doppler effects are exploited to enhance detection. Pulse Doppler radars utilize high PRFs to increases the average transmitted power and rely on target's Doppler frequency for detection. The increase in the average transmitted power leads to an improved SNR which helps the detection process. However, using high PRFs compromise the radar's ability to detect long range target because of range ambiguities associated with high PRF applications. Techniques such as using specialized Doppler filters to reject clutter are very effective and are often employed by pulse Doppler radars. Pulse Doppler radars can measure target Doppler frequency (or its range rate) fairly accurately and use the fact that ground clutter typically possesses limited Doppler shift when compared with moving targets to separate the two returns. Clutter filtering is used to remove both main-beam and altitude clutter returns, and fast moving target detection is done effectively by exploiting its Doppler frequency. In many modern pulse Doppler radars the limiting factor in detecting slow moving targets is not clutter but rather another source of noise referred to as phase noise generated from the receiver local oscillator instabilities.
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Krasnov, Oleg A., and Alexander G. Yarovoy. "Radar micro-Doppler of wind turbines: simulation and analysis using rotating linear wire structures." International Journal of Microwave and Wireless Technologies 7, no. 3-4 (June 2015): 459–67. http://dx.doi.org/10.1017/s1759078715000641.

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A simple electromagnetic model of wind-turbine's main structural elements as the linear wired structures is developed to simulate the temporal patterns of observed radar return Doppler spectra (micro-Doppler). Using the model, the micro-Doppler for different combinations of the turbines rotation frequency, radar pulse repetition frequency, and duration of the Doppler measurement interval are analyzed. The model is validated using the PARSAX radar experimental data. The model ability to reproduce the observed Doppler spectra main features can be used for development of signal-processing algorithms to suppress the wind-turbines clutter in modern Doppler radars.
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Wasserzier, Christoph. "Exploiting the Low Doppler Tolerance of Noise Radar to Perform Precise Velocity Measurements on a Short Set of Data." Signals 2, no. 1 (January 21, 2021): 25–40. http://dx.doi.org/10.3390/signals2010003.

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The extraction of velocity information from radar data by means of the Doppler effect is the driving factor for the investigations presented in this paper. A method for the quantification of the Doppler tolerance in continuous emission (CE) noise radar is introduced, addressing a current lack in literature within the frame of CE noise radars. It is shown that noise radar is highly sensitive to the Doppler effect, an issue that often results in a low Doppler tolerance especially for long coherent integration intervals. In general, the Doppler sensitivity is considered as a drawback but, in this paper, along with the absence of range-Doppler coupling in noise radar, it is turned into an advantage allowing for a very precise Doppler estimation. This new signal processing approach for Doppler extraction is detailed and its feasibility is proven on the basis of experimental data. The presented method requires much less data, i.e., target illumination time, than conventional Doppler analyses and, therefore, is beneficial in terms of radar resource management.
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Liou, Yu-Chieng, Howard B. Bluestein, Michael M. French, and Zachary B. Wienhoff. "Single-Doppler Velocity Retrieval of the Wind Field in a Tornadic Supercell Using Mobile, Phased-Array, Doppler Radar Data." Journal of Atmospheric and Oceanic Technology 35, no. 8 (August 2018): 1649–63. http://dx.doi.org/10.1175/jtech-d-18-0004.1.

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AbstractA three-dimensional data assimilation (3DVar) least squares–type single-Doppler velocity retrieval (SDVR) algorithm is utilized to retrieve the wind field of a tornadic supercell using data collected by a mobile, phased-array, Doppler radar [Mobile Weather Radar (MWR) 05XP] with very high temporal resolution (6 s). It is found that the cyclonic circulation in the hook-echo region can be successfully recovered by the SDVR algorithm. The quality of the SDVR analyses is evaluated by dual-Doppler syntheses using data collected by two mobile Doppler radars [Doppler on Wheels 6 and 7 (DOW6 and DOW7, respectively)]. A comparison between the SDVR analyses and dual-Doppler syntheses confirms the conclusion reached by an earlier theoretical analysis that because of the temporally discrete nature of the radar data, the wind speed retrieved by single-Doppler radar is always underestimated, and this underestimate occurs more significantly for the azimuthal (crossbeam) wind component than for the radial (along beam) component. However, the underestimate can be mitigated by increasing the radar data temporal resolution. When the radar data are collected at a sufficiently high rate, the azimuthal wind component may be overestimated. Even with data from a rapid scan, phased-array, Doppler radar, our study indicates that it is still necessary to calculate the SDVR in an optimal moving frame of reference. Finally, the SDVR algorithm’s robustness is demonstrated. Even with a temporal resolution (2 min) much lower than that of the phased-array radar, the cyclonic flow structure in the hook-echo region can still be retrieved through SDVR using data observed by DOW6 or DOW7, although a difference in the retrieved fields does exist. A further analysis indicates that this difference is caused by the location of the radars.
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RAO, P. RAJESH, S. KALYANA SUNDARAM, S. B. THAMPI, R. SURESH, and J. P. GUPTA. "An overview of first Doppler Weather Radar inducted in the cyclone detection network of India Meteorological Department." MAUSAM 55, no. 1 (January 19, 2022): 155–76. http://dx.doi.org/10.54302/mausam.v55i1.963.

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India Meteorological Department (IMD) maintains a wide network of radars for the detection and study of severe weather phenomena like cyclones, thunderstorms, gust front etc. and for deriving upper air wind profile. To keep pace with the fast developments in the field of weather radar technology, IMD is gradually replacing its conventional radars with digital radars, a few of them with Doppler capabilities. An S-band Doppler Weather Radar (DWR) has been inducted into India Meteorological Department’s (IMD) Cyclone Detection Radar (CDR) network recently at Chennai as a replacement to the outlived analogue S-band radar and is declared operational from 21 February 2002. Salient features, both hardware and software, of the radar are discussed in this article.
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Richter, C., H. Jeske, and G. Peters. "The Doppler radar as rain gauge." Meteorologische Zeitschrift 1, no. 5 (November 5, 1992): 229–35. http://dx.doi.org/10.1127/metz/1/1992/229.

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Dolan, Brenda A., and Steven A. Rutledge. "An Integrated Display and Analysis Methodology for Multivariable Radar Data." Journal of Applied Meteorology and Climatology 46, no. 8 (August 1, 2007): 1196–213. http://dx.doi.org/10.1175/jam2524.1.

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Abstract Polarimetric Doppler radars provide valuable information about the kinematic and microphysical structure of storms. However, in-depth analysis using radar products, such as Doppler-derived wind vectors and hydrometeor identification, has been difficult to achieve in (near) real time, mainly because of the large volumes of data generated by these radars, lack of quick access to these data, and the challenge of applying quality-control measures in real time. This study focuses on modifying and automating several radar-analysis and quality-control algorithms currently used in postprocessing and merging the resulting data from several radars into an integrated analysis and display in (near) real time. Although the method was developed for a specific network of four Doppler radars: two Weather Surveillance Radar-1988 Doppler (WSR-88D) radars (KFTG and KCYS) and two Colorado State University (CSU) research radars [Pawnee and CSU–University of Chicago–Illinois State Water Survey (CSU–CHILL)], the software is easily adaptable to any radar platform or network of radars. The software includes code to synthesize radial velocities to obtain three-dimensional wind vectors and includes algorithms for automatic quality control of the raw polarimetric data, hydrometeor identification, and rainfall rate. The software was successfully tested during the summers of 2004 and 2005 at the CSU–CHILL radar facility, ingesting data from the four-radar network. The display software allows users the ability to view mosaics of reflectivity, wind vectors, and rain rates, to zoom in and out of radar features easily, to create vertical cross sections, to contour data, and to archive data in real time. Despite the lag time of approximately 10 min, the software proved invaluable for diagnosing areas of intense rainfall, hail, strong updrafts, and other features such as mesocyclones and convergence lines. A case study is presented to demonstrate the utility of the software.
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Fujiyoshi, Yasushi, Koji Osumi, Masayuki Ohi, and Yoshinori Yamada. "Sea Ice Identification and Derivation of Its Velocity Field by X-Band Doppler Radar." Journal of Atmospheric and Oceanic Technology 30, no. 6 (June 1, 2013): 1240–49. http://dx.doi.org/10.1175/jtech-d-12-00155.1.

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Abstract In this study a 3D scanning X-band Doppler radar (XDR) was deployed near the coast of the Sea of Okhotsk, Hokkaido, Japan, in November 2005 to simultaneously observe sea ice and snow clouds. Doppler radars are commonly used to detect wind fields within precipitating clouds. However, thus far, there have been no reports of observing sea ice with Doppler radar. Making use of the radar reflectivity, Doppler velocity, and spectrum width, sea ice floes were identified under various weather conditions. Also presented is a new method that combines Doppler radar data and sea ice velocity—extracted using the cross-correlation method—to derive a high-spatial-resolution horizontal distribution of the velocity of sea ice floes. These methods will contribute to short-term forecasting of sea ice conditions and navigation through ice-covered seas and the development and verification of high-resolution dynamic sea ice models.
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Kollias, Pavlos, Mark A. Miller, Edward P. Luke, Karen L. Johnson, Eugene E. Clothiaux, Kenneth P. Moran, Kevin B. Widener, and Bruce A. Albrecht. "The Atmospheric Radiation Measurement Program Cloud Profiling Radars: Second-Generation Sampling Strategies, Processing, and Cloud Data Products." Journal of Atmospheric and Oceanic Technology 24, no. 7 (July 1, 2007): 1199–214. http://dx.doi.org/10.1175/jtech2033.1.

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Abstract The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program operates millimeter-wavelength cloud radars in several climatologically distinct regions. The digital signal processors for these radars were recently upgraded and allow for enhancements in the operational parameters running on them. Recent evaluations of millimeter-wavelength cloud radar signal processing performance relative to the range of cloud dynamical and microphysical conditions encountered at the ARM Program sites have indicated that improvements are necessary, including significant improvement in temporal resolution (i.e., less than 1 s for dwell and 2 s for dwell and processing), wider Nyquist velocities, operational dealiasing of the recorded spectra, removal of pulse compression while sampling the boundary layer, and continuous recording of Doppler spectra. A new set of millimeter-wavelength cloud radar operational modes that incorporate these enhancements is presented. A significant change in radar sampling is the introduction of an uneven mode sequence with 50% of the sampling time dedicated to the lower atmosphere, allowing for detailed characterization of boundary layer clouds. The changes in the operational modes have a substantial impact on the postprocessing algorithms that are used to extract cloud information from the radar data. New methods for postprocessing of recorded Doppler spectra are presented that result in more accurate identification of radar clutter (e.g., insects) and extraction of turbulence and microphysical information. Results of recent studies on the error characteristics of derived Doppler moments are included so that uncertainty estimates are now included with the moments. The microscale data product based on the increased temporal resolution of the millimeter-wavelength cloud radars is described. It contains the number of local maxima in each Doppler spectrum, the Doppler moments of the primary peak, uncertainty estimates for the Doppler moments of the primary peak, Doppler moment shape parameters (e.g., skewness and kurtosis), and clear-air clutter flags.
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Dissertations / Theses on the topic "Doppler radar"

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Geladakis, Dimitrios N. "Comparison of the step frequency radar with the conventional constant frequency radars." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1996. http://handle.dtic.mil/100.2/ADA328272.

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Thesis (M.S. in Electrical Engineering) Naval Postgraduate School, December 1996.
"December 1996." Thesis advisor(s): Gurnam S. Gill. Includes bibliographical references (p. 45). Also available online.
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Chua, Cheng Lock Charles. "Doppler-only synthetic aperture radar." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FChua.pdf.

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Thesis (M.S. in Combat Systems Sciences and Technology)--Naval Postgraduate School, December 2006.
Thesis Advisor(s): Brett Borden, Donald Walters. "December 2006." Includes bibliographical references (p. 69-70). Also available in print.
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Agirman, Handan. "Waveform Design For Pulse Doppler Radar." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/2/12606840/index.pdf.

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ABSTRACT WAVEFORM DESIGN FOR PULSE DOPPLER RADAR AgIRMAN, Handan M.S., Department of Electrical and Electronics Engineering Supervisor: Prof. Dr. Mete Severcan December 2005, 100 pages This study is committed to the investigation of optimum waveforms for a pulse doppler radar which uses a non linear high power amplifier in the transmitter. The optimum waveform is defined as the waveform with the lowest peak and integrated side lobe level, the narrowest main lobe in its autocorrelation and the narrowest bandwidth in its spectrum. The Pulse Compression method is used in radar systems since it is more advantageous in terms of the resolution. Among all pulse compression methods, the main focus of this study is on Phase Coding. Two types of radar waveforms assessed throughout this study are Discrete Phase Modulated Waveforms and Continuous Phase Modulated Waveforms. The continuous phase modulated waveforms are arranged under two titles: the memoryless phase modulated waveform and the waveform modulated with memory. In order to form memoryless continuous phase waveforms, initially, discrete phase codes are obtained by using Genetic Algorithm. Following this process, a new phase shaping pulse is defined and applied on the discrete phase waveforms. Among the applicable modulation with memory techniques, Continuous Phase Modulation maintains to be the most appropriate. The genetic algorithm is used to find different lengths of optimum data sequences which form the continuous phase scheme.
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Aygar, Alper. "Doppler Radar Data Processing And Classification." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609890/index.pdf.

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In this thesis, improving the performance of the automatic recognition of the Doppler radar targets is studied. The radar used in this study is a ground-surveillance doppler radar. Target types are car, truck, bus, tank, helicopter, moving man and running man. The input of this thesis is the output of the real doppler radar signals which are normalized and preprocessed (TRP vectors: Target Recognition Pattern vectors) in the doctorate thesis by Erdogan (2002). TRP vectors are normalized and homogenized doppler radar target signals with respect to target speed, target aspect angle and target range. Some target classes have repetitions in time in their TRPs. By the use of these repetitions, improvement of the target type classification performance is studied. K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) algorithms are used for doppler radar target classification and the results are evaluated. Before classification PCA (Principal Component Analysis), LDA (Linear Discriminant Analysis), NMF (Nonnegative Matrix Factorization) and ICA (Independent Component Analysis) are implemented and applied to normalized doppler radar signals for feature extraction and dimension reduction in an efficient way. These techniques transform the input vectors, which are the normalized doppler radar signals, to another space. The effects of the implementation of these feature extraction algoritms and the use of the repetitions in doppler radar target signals on the doppler radar target classification performance are studied.
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Smith, G. E. "Radar target micro-Doppler signature classification." Thesis, University College London (University of London), 2008. http://discovery.ucl.ac.uk/18688/.

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This thesis reports on research into the field of Micro-Doppler Signature (μ-DS) based radar Automatic Target Recognition (ATR) with additional contributions to general radar ATR methodology. The μ-DS based part of the research contributes to three distinct areas: time domain classification; frequency domain classification; and multiperspective μ-DS classification that includes the development of a theory for the multistatic μ-DS. The contribution to general radar ATR is the proposal of a methodology to allow better evaluation of potential approaches and to allow comparison between different studies. The proposed methodology is based around a “black box” model of a radar ATR system that, critically, includes a threshold to detect inputs that are previously unknown to the system. From this model a set of five evaluation metrics are defined. The metrics increase the understanding of the classifier’s performance from the common probability of correct classification, that reports how often the classifier correctly identifies an input, to understanding how reliable it is, how capable it is of generalizing from the reference data, and how effective its unknown input detection is. Additionally, the significance of performance prediction is discussed and a preliminary method to estimate how well a classifier should perform is developed. The proposed methodology is then used to evaluate the μ-DS based radar ATR approaches considered. The time domain classification investigation is based around using Dynamic Time Warping (DTW) to identify radar targets based on their μ-DS. DTW is a speech processing technique that classifies data series by comparing them with a pre-classified reference dataset. This is comparable to the common k-Nearest Neighbour (k-NN) algorithm, so k-NN is used as a benchmark against which to evaluate DTW’s performance. The DTW approach is observed to work well. It achieved high probability of correct classification and reliability as well as being able to detect inputs of unknown class. However, the classifier’s ability to generalize from the reference data is less impressive and it performed only slightly better than a random selection from the possible output classes. Difficulties in classifying the μ-DS in the time domain are identified from the k-NN results prompting a change to the frequency domain. Processing the μ-DS in the frequency domain permitted the development of an advanced feature extraction routine to maximize the separation of the target classes and therefore reduce the effort required to classify them. The frequency domain also permitted the use of the performance prediction method developed as part of the radar ATR methodology and the introduction of a na¨ıve Bayesian approach to classification. The results for the DTW and k-NN classifiers in the frequency domain were comparable to the time domain, an unexpected result since it was anticipated that the μ-DS would be easier to classify in the frequency domain. However, the naıve Bayesian classifier produced excellent results that matched with the predicted performance suggesting it could not be bettered. With a successful classifier, that would be suitable for real-world use, developed attention turned to the possibilities offered by the multistatic μ-DS. Multiperspective radar ATR uses data collected from different target aspects simultaneously to improve classification rates. It has been demonstrated successful for some of the alternatives to μ-DS based ATR and it was therefore speculated that it might improve the performance of μ-DS ATR solutions. The multiple perspectives required for the classifier were gathered using a multistatic radar developed at University College London (UCL). The production of a dataset, and its subsequent analysis, resulted in the first reported findings in the novel field of the multistatic μ-DS theory. Unfortunately, the nature of the radar used resulted in limited micro-Doppler being observed in the collected data and this reduced its value for classification testing. An attempt to use DTW to perform multiperspective μ-DS ATR was made but the results were inconclusive. However, consideration of the improvements offered by multiperspective processing in alternative forms of ATR mean it is still expected that μ-DS based ATR would benefit from this processing.
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Crowley, G. "Doppler radar studies of the Antarctic ionosphere." Thesis, University of Leicester, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.353168.

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Sjöholm, Olof. "Integrated CMOS Doppler Radar : Power Amplifier Mixer." Thesis, Linköpings universitet, Elektroniska Kretsar och System, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-129105.

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This thesis is based on a paper by V. Issakov, presented 2009, where a circuit of a merged power amplifier mixer solution was demonstrated. This work takes that solution and simplifies it for the use at a lower frequency. The implementation target is a Doppler radar application in CMOS that can detect humans in a range of 5 to 15 meters. This could be used as a burglar alarm or an automatic light switch. The report will present the background of Issakov’s work, basic theory used and the implementation of the final design. Simulations will show that the solution presented work, with a 15 dB conversion loss. This design performs well compared to reference mixers. With this report it will be shown that it is possible to make a simple and compact Doppler radar system in CMOS.
Denna avhandling bygger på en artikel av V. Issakov, presenterad 2009, där en lösning för att sammanslå en effektförstärkare med en mixer till en krets visades. Detta arbete tar denna lösning och förenklar det för användning vid en lägre frekvens. Målet är att implementera en dopplerradar i CMOS som kan detektera människor inom ett avstånd på 5 till 15 meter. Denna radar skulle kunna användas som ett inbrottslarm eller en automatisk strömbrytare. Rapporten kommer att presentera bakgrunden från Issakov’s arbete, grundläggande teori som används och genomförandet av det slutliga kretsschemat. Simuleringar visar att den presenterade lösningen fungerar, med en 15 dB konverteringsförlust. Denna konstruktion presterar väl jämfört med referens mixrar. Med denna rapport visas det att det är möjligt att göra ett enkelt och kompakt dopplerradarsystem i CMOS.
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Van, Eeden Willem Daniel. "Human and animal classification using Doppler radar." Diss., University of Pretoria, 2005. http://hdl.handle.net/2263/66252.

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South Africa is currently struggling to deal with a significant poaching and livestock theft problem. This work is concerned with the detection and classification of ground based targets using radar micro- Doppler signatures to aid in the monitoring of borders, nature reserves and farmlands. The research starts of by investigating the state of the art of ground target classification. Different radar systems are investigated with respect to their ability to classify targets at different operating frequencies. Finally, a Gaussian Mixture Model Hidden Markov Model based (GMM-HMM) classification approach is presented and tested in an operational environment. The GMM-HMM method is compared to methods in the literature and is shown to achieve reasonable (up to 95%) classification accuracy, marginally outperforming existing ground target classification methods.
Dissertation (MEng)--University of Pretoria, 2017.
Electrical, Electronic and Computer Engineering
MEng
Unrestricted
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Dilsaver, Benjamin Walter. "Experiments with GMTI Radar using Micro-Doppler." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/3678.

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As objects move, their changing shape produces a signature that can be measured by a radar system. That signature is called the micro-Doppler signature. The micro-Doppler signature of an object is a distinguishing characteristic for certain classes of objects. In this thesis features are extracted from the micro-Doppler signature and are used to classify objects. The scope of the objects is limited to humans walking and traveling vehicles. The micro-Doppler features are able to distinguish the two classes of objects. With a sufficient amount of training data, the micro-Doppler features may be used with learning algorithms to predict unknown objects detected by the radar with high accuracy.
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Kavanagh, Patricia F. "Doppler centroid ambiguity estimation for synthetic aperture radar." Thesis, University of British Columbia, 1985. http://hdl.handle.net/2429/25075.

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For a synthetic aperture radar (SAR) system, the Doppler centroid is the azimuth Doppler frequency received from a point scatterer centered in the azimuth antenna pattern. This parameter is required by the SAR processor in order to properly focus SAR images. Since the azimuth Doppler spectrum is weighted by the azimuth antenna pattern, the Doppler centroid can be determined by locating the peak of the Doppler spectrum. This measurement, however, is ambiguous because the azimuth Doppler spectrum is aliased by the radar pulse repetition frequency (PRF). To resolve the ambiguity, the antenna beam angle, which determines the Doppler centroid, is measured; the accuracy of this measurement must be high enough to determine the Doppler centroid to within ±PRF/2. For some SAR systems, such as the future Radarsat system, the beam angle measurement must be very accurate; this can be technically infeasible or too costly to implement. This thesis examines an alternative approach to resolving the Doppler centroid ambiguity which does not require accurate beam angle measurement In most SAR processors, several partial azimuth aperture "looks" are processed, rather than a single long aperture, in order to yield a final SAR image with reduced speckle noise. If the Doppler centroid is in error by an integer number of PRFs, then the SAR looks will be defocussed and misregistered in range. The degree of misregistration depends on with which Doppler centroid ambiguity the data is processed. The new method for Doppler centroid ambiguity estimation measures the range displacement of SAR looks using a cross-correlation of looks in the range direction. The theoretical background and details of the new method are discussed. The effects of differing terrain types, wave motion, and errors in the azimuth frequency modulation (FM) rate are addressed. The feasibility of the approach is demonstrated by testing the cross-correlation algorithm on available Seasat data processed with simulated Doppler centroid ambiguity errors. The Seasat analysis is extrapolated to the Radarsat system with favourable results.
Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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Books on the topic "Doppler radar"

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Boric-Lubecke, Olga, Victor M. Lubecke, Amy D. Droitcour, Byung-Kwon Park, and Aditya Singh, eds. Doppler Radar Physiological Sensing. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2016. http://dx.doi.org/10.1002/9781119078418.

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1935-, Morris G. V., and Harkness L. 1956-, eds. Airborne pulsed doppler radar. 2nd ed. Boston: Artech House, 1996.

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Morris, G. V. Airborne pulsed Doppler radar. Norwood, MA: Artech House, 1988.

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United States. Office of Federal Coordinator for Meteorological Services and Supporting Research, ed. Doppler radar meteorological observations. Rockville, Md: Federal Coordinator for Meteorological Services and Supporting Research, 1990.

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United States. Office of Federal Coordinator for Meteorological Services and Supporting Research., ed. Doppler radar meteorological observations. Washington, DC: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Office of the Federal Coordinator for Meteorological Services and Supporting Research, 1990.

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Schleher, D. Curtis. MTI and pulsed doppler radar. Boston: Artech House, 1991.

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S, Zrnić Dušan, ed. Doppler radar and weather observations. 2nd ed. Mineola, N.Y: Dover Publications, 2006.

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S, Zrnić Dušan, ed. Doppler radar and weather observations. 2nd ed. San Diego: Academic Press, 1993.

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P, McKinney, Ozmen F, and Langley Research Center, eds. Analysis of Doppler radar windshear data. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1989.

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United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., ed. Designing clutter rejection filters with complex coefficients for airborne pulsed Doppler weather radar. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1993.

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Book chapters on the topic "Doppler radar"

1

Brown, Rodger A. "Doppler Weather Radar." In Encyclopedia of Natural Hazards, 188. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-1-4020-4399-4_96.

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Ryzhkov, Alexander V., and Dusan S. Zrnic. "Polarimetric Doppler Radar." In Springer Atmospheric Sciences, 19–40. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05093-1_2.

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Yavari, Ehsan, Olga Boric-Lubecke, and Shuhei Yamada. "Radar Principles." In Doppler Radar Physiological Sensing, 21–38. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2016. http://dx.doi.org/10.1002/9781119078418.ch2.

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Nichols, T. R., P. I. Joe, and C. L. Crozier. "Canada’s Operational Doppler Radar." In Weather Radar Networking, 278–85. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0551-1_31.

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Morris, Guy V. "Doppler Frequency Tracking." In Principles of Modern Radar, 598–617. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1971-9_19.

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James, D. A. "Pulse-Doppler." In Radar Homing Guidance for Tactical Missiles, 96–105. London: Macmillan Education UK, 1986. http://dx.doi.org/10.1007/978-1-349-08602-3_7.

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Singh, Aditya, Byung-Kwon Park, Olga Boric-Lubecke, Isar Mostafanezhad, and Victor M. Lubecke. "Physiological Doppler Radar Overview." In Doppler Radar Physiological Sensing, 69–94. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2016. http://dx.doi.org/10.1002/9781119078418.ch4.

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Kiriazi, John, Olga Boric-Lubecke, Shuhei Yamada, Victor M. Lubecke, and Wansuree Massagram. "Doppler Radar Physiological Assessments." In Doppler Radar Physiological Sensing, 171–206. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2016. http://dx.doi.org/10.1002/9781119078418.ch7.

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Ng, Herman Jalli. "Doppler Radar Sensor Platform." In Handbook of Biochips, 1–23. New York, NY: Springer New York, 2020. http://dx.doi.org/10.1007/978-1-4614-6623-9_53-1.

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Ng, Herman Jalli. "Doppler Radar Sensor Platform." In Handbook of Biochips, 845–67. New York, NY: Springer New York, 2022. http://dx.doi.org/10.1007/978-1-4614-3447-4_53.

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Conference papers on the topic "Doppler radar"

1

Martin, J. "Range and Doppler accuracy improvement for pulse Doppler radar." In Radar Systems (RADAR 97). IEE, 1997. http://dx.doi.org/10.1049/cp:19971713.

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Wei, Yinsheng, and Zhineng Mao. "Novel Range-Doppler Processing and Waveform Design Method for Extending Unambiguous Doppler." In 2018 International Conference on Radar (RADAR). IEEE, 2018. http://dx.doi.org/10.1109/radar.2018.8557307.

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Yarman, Can Evren, and Birsen Yazici. "Doppler Synthetic Aperture Hitchhiker imaging." In 2008 IEEE Radar Conference (RADAR). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4721085.

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Pribic, R. "Doppler processing on irregular PRT." In 2002 International Radar Conference (Radar 2002). IEE, 2002. http://dx.doi.org/10.1049/cp:20020295.

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Smith, Graeme E., Karl Woodbridge, and Chris J. Baker. "Multistatic Micro-Doppler Signature of personnel." In 2008 IEEE Radar Conference (RADAR). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4721060.

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Gregers-Hansen, Vilhelm, and Mai T. Ngo. "EMI repair in pulse doppler radar." In 2008 IEEE Radar Conference (RADAR). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4720728.

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Xu, Shengzhi, and Alexander Yarovoy. "Doppler Shifts Mitigation for PMCW Signals." In 2019 International Radar Conference (RADAR). IEEE, 2019. http://dx.doi.org/10.1109/radar41533.2019.171290.

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Smith, Matthew A. "On Doppler measurements for tracking." In 2008 International Conference on Radar (Radar 2008). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4653978.

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Yao, I., E. M. Hauser, C. A. Bouman, and A. M. Chiang. "Hybrid Signal Processor for Wideband Radar*." In Picosecond Electronics and Optoelectronics. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/peo.1985.wb2.

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The signal processing task for radar systems with large instantaneous bandwidth and wide range coverage stresses the throughput rate of conventional digital processors. In this paper, a hybrid analog signal processor for wideband pulse-Doppler radar1 is described. It offers the potential of a compact, high-throughput processor. In the processor, three types of analog signal processing devices are incorporated. They are: (1) a surface-acoustic-wave (SAW) convolver2 to perform programmable pulse compression for radar signals with 200-MHz instantaneous bandwidth in order to provide target range information with 0.75-m resolution, (2) optoelectronic sample-and-hold (S/H) circuits3 to perform the range gating function and the buffering of the sampled data into the Doppler processor, and (3) charge-coupled-device (CCD) matrix-matrix-product (MMP) chips4 to perform Doppler Fourier analysis in order to provide target velocity information.
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Gorelov, E. P. "Autodyne Coherent Doppler Lidars." In Coherent Laser Radar. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/clr.1991.wb5.

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Autodyne coherent lidars, i.e., the lidars with intracavity reception of the echo-signals proved to be of efficient for studying the atmosphere1-3. They possess high sensitivity and high noise immunity. They make it possible to determine few parameters in question simultaneously, namely: the absorption along the path, the distance to the retroreflector and its velocity. The ways for determining the above parameters are described.
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Reports on the topic "Doppler radar"

1

Snyder, Donald L. Delay-Doppler Radar Imaging. Fort Belvoir, VA: Defense Technical Information Center, November 1986. http://dx.doi.org/10.21236/ada176626.

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SCHWARTZ ELECTRO-OPTICS INC ORLANDO FL. One Micron Laser Doppler Radar. Fort Belvoir, VA: Defense Technical Information Center, February 1989. http://dx.doi.org/10.21236/ada207891.

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Doerry, Armin W. Radar Doppler Processing with Nonuniform Sampling. Office of Scientific and Technical Information (OSTI), July 2017. http://dx.doi.org/10.2172/1373645.

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Sashegyi, Keith D. Shipboard Data Assimilation System/Doppler Radar. Fort Belvoir, VA: Defense Technical Information Center, September 2000. http://dx.doi.org/10.21236/ada610257.

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Zhao, Allen. Improved Doppler Radar/Satellite Data Assimilation. Fort Belvoir, VA: Defense Technical Information Center, September 2009. http://dx.doi.org/10.21236/ada531653.

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Zhao, Allen. Improved Doppler Radar/Satellite Data Assimilation. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada533027.

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Zhao, Allen. Improved Doppler Radar/Satellite Data Assimilation. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada541360.

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Zhao, Allen. Ensemble Assimilation of Doppler Radar Observations. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada541829.

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Barker, Edward H., and Keith D. Sashegyi. Shipboard Data Assimilation System/Doppler Radar. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada630755.

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Zhao, Allen. Shipboard Data Assimilation System/Doppler Radar. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada631042.

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