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Journal articles on the topic 'Tracking radar Data processing'
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1
Hero, A. "Radar data processing: Vol. I - Introduction and tracking." IEEE Transactions on Acoustics, Speech, and Signal Processing 34, no. 5 (October 1986): 1350–51. http://dx.doi.org/10.1109/tassp.1986.1164939.
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Morgera, Salvatore D. "Radar data processing — volume I: Introduction and tracking." Signal Processing 11, no. 4 (December 1986): 413–15. http://dx.doi.org/10.1016/0165-1684(86)90084-8.
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Kim, Beom-Hun, Seung-Jo Han, Goo-Rak Kwon, and Jae-Young Pyun. "Signal Processing for Tracking of Moving Object in Multi-Impulse Radar Network System." International Journal of Distributed Sensor Networks 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/536841.
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Indoor positioning systems (IPSs) have been discussed for use in entertainment, home automation, rescue, surveillance, and healthcare applications. In this paper, we present an IPS that uses an impulse radio-ultra-wideband (IR-UWB) radar network. This radar network system requires at least two radar devices to determine the current coordinates of a moving person. However, one can enlarge the monitoring area by adding more radar sensors. To track moving targets in indoor environments, for example, patients in hospitals or intruders in a home, signal processing procedures for tracking should be applied to the raw data measured using IR-UWB radars. This paper presents the signal processing method required for robust target tracking in a radar network, that is, an iterative extended Kalman filter- (IEKF-) based object tracking method, which uses two IR-UWB radars to measure the coordinates of the targets. The proposed IEKF tracking method is compared to the conventional extended Kalman filter (EKF) method. The results verify that the IEKF method improves the performance of 2D target tracking in a real-time system.
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Chen, Weishi. "Interactive processing of radar target detection and tracking." Aircraft Engineering and Aerospace Technology 90, no. 9 (November 14, 2018): 1337–45. http://dx.doi.org/10.1108/aeat-07-2016-0115.
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Purpose An interactive processing scheme is proposed to improve the target detection probability as well as the tracking performance of the radar system. Design/methodology/approach Firstly, with the spatial-correlated features extracted from the foreground and background statistical models, the thresholds were adapted to distinguish the dim small targets from clutters in the complex incoherent radar images. Then, the target trajectories were constructed with the target tracking algorithm. According to the temporal correlation with the target life cycle, the thresholding values were modified in the neighbourhood of the predicted positions to improve the detection sensitivity in these areas during the tracking process. Finally, the temporal-correlated features of the remained clutters were used to further reduce the false alarm rate. Findings The proposed algorithm was applied on the simulated data, as well as the image sequences obtained with the incoherent marine radars. The detection results demonstrated that the interactive algorithm could detect and track the dim small targets with relatively low false alarm rate. Practical implications The interactive processing scheme could be applied for low-altitude airspace surveillance with incoherent marine radar. Originality/value The proposed scheme outperforms the classical radar target detection algorithms and the state-of-the-art image processing algorithms for video-based surveillance.
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Bureneva, O. I., I. G. Gorbunov, G. V. Komarov, A. A. Konovalov, M. S. Kupriyanov, and Yu A. Shichkina. "A Prototype of Automotive 77 GHz Radar." Journal of the Russian Universities. Radioelectronics 24, no. 3 (June 24, 2021): 22–38. http://dx.doi.org/10.32603/1993-8985-2021-24-3-22-38.
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Introduction. Automotive radars are the main tools for providing traffic safety. The development of such radars involve a number of technical difficulties due to the manufacture of high-precision extremely high-frequency (EHF) printed circuit boards. To facilitate the process of creating such devices, the existing algorithms for radar information processing should be debugged using prototypes from manufacturers of mm-band transceivers. However, the parameters of such boards are not known in advance, and the actual operating conditions of the as-produced automotive radars raise new challenges to target tracking algorithms. Therefore, checking the performance of such boards is a relevant research problem.Aim. To evaluate the performance of a millimeter-wave automotive radar prototype and to test target tracking algorithms using this prototype.Materials and methods. An original target tracking method was used, which considers the constraints on the use of additional data sources about the radar carrier movement.Results. An experimental performance evaluation of a 77 GHz automotive radar prototype was carried out. The effectiveness of primary processing for the target class “vehicle” in the millimetre range was checked. Original algorithms for target tracking were proposed and tested.Conclusion. The obtained results show that the prototype board of a transceiver chip is capable of testing tracking algorithms without creating an own automotive radar prototype. Thus, the developmental process can be significantly shortened. Moreover, after creating a hardware solution, the developer obtains a reference device to test and configure an own product without using extremely expensive and rare EHF equipment.
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Palamarchuk, Yu O., S. V. Ivanov, and I. G. Ruban. "The digitizing algorithm for precipitation in the atmosphere on the base of radar measurements." Ukrainian hydrometeorological journal, no. 18 (October 29, 2017): 40–47. http://dx.doi.org/10.31481/uhmj.18.2016.05.
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There is an increasing demand for automated high-quality very-short-range forecasts and nowcasts of precipitation on small scales and at high update frequencies. Current prediction systems use different methods of determining precipitation such as area tracking, individual cell tracking and numerical models. All approaches are based on radar measurements. World-leading manufactories of meteorological radars and attendant visualization software are introduced in the paper. Advantages of the numerical modelling against inertial schemes designed on statistical characteristics of convective processes are outlined. On this way, radar data assimilation systems as a necessary part of numerical models are intensively developed. In response to it, the use of digital formats for processing of radar measurements in numerical algorithms became important. In the focus of this work is the developing of a unified code for digital processing of radar signals at the preprocessing, filtration, assimilation and numerical integration steps. The proposed code also includes thinning, screening or superobbing radar data before exploring them for the assimilation procedures. The informational model manages radar data flows in the metadata and binary array forms. The model constitutes an official second-generation European standard exchange format for weather radar datasets from different manufactories. Results of radar measurement processing are presented for both, the single radar and radar overlying network.
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Daliakopoulos, Ioannis N., and Ioannis K. Tsanis. "A weather radar data processing module for storm analysis." Journal of Hydroinformatics 14, no. 2 (July 14, 2011): 332–44. http://dx.doi.org/10.2166/hydro.2011.118.
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A pre- and post-processing weather radar data module was developed in the Matlab suite of software with GIS data exchange abilities for storm event analysis. During pre-processing, each radar sweep is converted from spherical to Cartesian coordinates in the desired temporal and spatial resolution. The module's functionality in post processing includes radar data display, geo-referencing over GIS maps, data filtering with the Wiener filter and single or multiple sweep processing. The user can perform individual storm cell detection and tracking, resulting in the storm's average velocity and track length. The tested methods are modifications of the LoG (Laplacian of the Gaussian) blob detection method and a Brownian particle trajectory linking algorithm. Radar reflectivity factor (Z) data can be referenced over predefined rainfall (R) gauges in order to determine the radar Z–R equation parameters. The user can also produce spatially distributed precipitation estimates by using standard Z–R equations from the literature. The module's functionality is demonstrated using data from a rainfall event captured by the NSA Souda Bay C-Band radar during a storm in October 2006. Results show that the Rosenfeld Tropical Z–R equation is the one that gives a satisfactory description of the spatial and temporal precipitation distribution of the investigated event.
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Hong, Yong Bin, Cheng Fa Xu, Mei Guo Gao, and Li Zhi Zhao. "A High-Performance Signal Processing System for Monopulse Tracking Radar." Advanced Materials Research 383-390 (November 2011): 471–75. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.471.
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A radar signal processing system characterizing high instantaneous dynamic range and low system latency is designed based on a specifically developed signal processing platform. Instantaneous dynamic range loss is a critical problem when digital signal processing is performed on fixed-point FPGAs. In this paper, the problem is well resolved by increasing the wordlength according to signal-to-noise ratio (SNR) gain of the algorithms through the data path. The distinctive software structure featuring parallel pipelined processing and “data flow drive” reduces the system latency to one coherent processing interval (CPI), which significantly improves the maximum tracking angular velocity of the monopulse tracking radar. Additionally, some important electronic counter-countermeasures (ECCM) are incorporated into this signal processing system.
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Fiscante, Nicomino, Pia Addabbo, Carmine Clemente, Filippo Biondi, Gaetano Giunta, and Danilo Orlando. "A Track-Before-Detect Strategy Based on Sparse Data Processing for Air Surveillance Radar Applications." Remote Sensing 13, no. 4 (February 12, 2021): 662. http://dx.doi.org/10.3390/rs13040662.
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In this paper we consider the tracking problem of a moving target competing against noise and clutter in a surveillance radar scenario. For a single array-antenna multiple-target tracking system and according to the Track-Before-Detect paradigm, we present a novel approach based on a three-stage processing chain that involves the Sparse Learning via Iterative Minimization algorithm, the k-means clustering method and the ad hoc detector by exploiting the sparse nature of the operating scenario. Under the latter assumption, the detection strategy declares the presence of targets subsequently to the retrieval of their corresponding tracks performed by jointly processing the received echoes of multiple consecutive radar scans. Simulation results show that the proposed approach is able to provide good tracking and detection capabilities for different multiple target trajectories with low Signal-to-Interference-plus-Noise ratio and results in providing advantages when compared to a number of other reference Track-Before-Detect strategies based on sparse data processing techniques.
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Nikolic, Dejan, Nikola Stojkovic, Pavle Petrovic, Nikola Tosic, Nikola Lekic, Zoran Stankovic, and Nebojsa Doncov. "The high frequency surface wave radar solution for vessel tracking beyond the horizon." Facta universitatis - series: Electronics and Energetics 33, no. 1 (2020): 37–59. http://dx.doi.org/10.2298/fuee2001037n.
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With maximum range of about 200 nautical miles (approx. 370 km) High Frequency Surface Wave Radars (HFSWR) provide unique capability for vessel detection far beyond the horizon without utilization of any moving platforms. Such uniqueness requires design principles unlike those usually used in microwave radar. In this paper the key concepts of HFSWR based on Frequency Modulated Continuous (FMCW) principles are presented. The paper further describes operating principles with focus on signal processing techniques used to extract desired data. The signal processing describes range and Doppler processing but focus is given to the Digital Beamforming (DBF) and Constant False Alarm Rate (CFAR) models. In order to better present the design process, data obtained from the HFSWR sites operating in the Gulf of Guinea are used.
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Galajda, Pavol, Alena Galajdova, Stanislav Slovak, Martin Pecovsky, Milos Drutarovsky, Marek Sukop, and Ihab BA Samaneh. "Robot vision ultra-wideband wireless sensor in non-cooperative industrial environments." International Journal of Advanced Robotic Systems 15, no. 4 (July 1, 2018): 172988141879576. http://dx.doi.org/10.1177/1729881418795767.
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In this article, the ultra-wideband technology for localization and tracking of the robot gripper (behind the obstacles) in industrial environments is presented. We explore the possibilities of ultra-wideband radar sensor network employing the centralized data fusion method that can significantly improve tracking capabilities in a complex environment. In this article, we present ultra-wideband radar sensor network hardware demonstrator that uses a new wireless ultra-wideband sensor with an embedded controller to detect and track online or off-line movement of the robot gripper. This sensor uses M-sequence ultra-wideband radars front-end and low-cost powerful processors on a system on chip with the advanced RISC machines (ARM) architecture as a main signal processing block. The ARM-based single board computer ODROID-XU4 platform used in our ultra-wideband sensor can provide processing power for the preprocessing of received raw radar signals, algorithms for detection and estimation of target’s coordinates, and finally, compression of data sent to the data fusion center. Data streams of compressed target coordinates are sent from each sensor node to the data fusion center in the central node using standard the wireless local area network (WLAN) interface that is the feature of the ODROID-XU4 platform. The article contains experimental results from measurements where sensors and antennas are located behind the wall or opaque material. Experimental testing confirmed capability of real-time performance of developed ultra-wideband radar sensor network hardware and acceptable precision of software. The introduced modular architecture of ultra-wideband radar sensor network can be used for fast development and testing of new real-time localization and tracking applications in industrial environments.
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Parshutkin, Andrey, Dmitry Levin, and Aleksey Galandzovskiy. "Simulation model of radar data processing in a station network under signal-like interference." Information and Control Systems, no. 6 (January 16, 2020): 22–31. http://dx.doi.org/10.31799/1684-8853-2019-6-22-31.
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Introduction: Radar stations, when tracking targets in a complex interference environment, form not only target marks but also false marks. A well-developed theory and technique of noise stability is not useful under signal-like interference caused by re-reflections, multi-path propagation or retransmission of the probing signals. The reliability of radar information processing under signal-like interference can be improved by joint processing of data from several spaced posts in a radar station network. Purpose: development of а simulation model which would allow you to estimate the effectiveness of radar target selection by spatial rating of its measured positions, with joint processing of the radar information obtained from two spaced radar stations. Results: We have implemented the framework of joint radar data processing for target selection in a radar station network under signal-like interference. The selection is based on using the information about the coincidence of radar target coordinates measured by spaced radar stations. A simulation model is developed to estimate the target selection probability under signal-like interference during the joint processing of data from two spaced radar stations, by analyzing the coincidence of the measured coordinates of the targets. It has been found out how the target selection probability depends on the noise interference power and the average density of false marks in the range channels of two spaced radar stations. Practical relevance: The simulation results demonstrate the possibility of increasing the range of radar target detection by network radar stations under signal-like interference, and the efficiency of using the information about coincidence of radar target coordinates measured by spaced radar stations, which is better than using only the signal features of radar target selection on the background of false marks.
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ALSAKA, Y. A., L. A. YOUNG, and M. HAMID. "HIGH RESOLUTION MONOPULSE RADAR TRACKING SYSTEM." Journal of Circuits, Systems and Computers 02, no. 04 (December 1992): 305–21. http://dx.doi.org/10.1142/s0218126692000192.
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High resolution radar techniques are applied to the problem of resolving a multiple target array and locating its geometric center without the usual biasing toward the brightest scatterer. This result is accomplished using monopulse radar techniques combined with high resolution stepped frequency pulse train signal processing in an angle tracking noncoherent high resolution radar. The center of each uniquely separated pair of point targets is calculated by examining the crosscorrelation function of the sum and difference channels. The autocorrelation of the sum channel is used to normalize the crosscorrelation data thereby eliminating the effects of the different targets’ radar cross sections (RCS). The zero separation term of the error function (dc term) remains biased toward the bigger scatterer, even after normalization. The nonzero terms (ac terms) are the cross range distances from the antenna’s boresight to each scatterer and are independent of their RCS. By simply dropping the zero separation term and averaging the remaining terms together, the aimpoint becomes the unbiased geometric center of the array.
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Chen, Bo Lin, and Yun Tao Li. "Design of Analysis Software for Measured RCS Data." Applied Mechanics and Materials 333-335 (July 2013): 172–77. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.172.
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Radar cross section is an extremely important parameter in narrowband radar application for space target detection, tracking, and identification, as well as for the purpose of threat assessment. An analysis algorism, together with related software for measured RCS data has been developed to extract information from the original data. Some analyzing methods for measured RCS data were introduced. The playback visual simulation process and data processing were elaborated, so as to handle the processing of software program. Finally the software running results were analyzed. The experiment results showed that the software could be used for the issue of analysis of measured RCS data in a reliable and systematical way. As a result, it provides us with a strong guarantee for space surveillance.
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Džunda, Milan, Peter Dzurovčin, Peter Kaľavský, Peter Korba, Zoltán Cséfalvay, and Michal Hovanec. "The UWB Radar Application in the Aviation Security Systems." Applied Sciences 11, no. 10 (May 17, 2021): 4556. http://dx.doi.org/10.3390/app11104556.
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In the process of our research, we have identified new methods of processing ultra-wide-band (UWB) radar signals and possibilities of the UWB radar use in aviation security systems. We paid our main attention to finding new algorithms for tracking the movement of a person behind an obstacle using the UWB radar. Such UWB radar application is typical for tracking the movement of people behind obstacles in case of security forces intervention at an airport. In the research process, we used methods of analysis, synthesis, and measured data from the performed experiment. The main contribution of the paper is the development of new algorithms for locating the movement of a person behind an obstacle using a straight- line method in the case of using two independent UWB radar systems. The article did not examine the accuracy of determining the position of a person behind the obstacle. We found that when applying the Kalman filter after signal processing by the straight-line method, the trajectory of the person’s movement behind the obstacle was smoother. The results of processing the measurement signals of UWB radar by the linear method have shown that this method is applicable to tracking a person behind an obstacle and can be used in aviation security systems.
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Zhao, Yan Li, Xiao Zun Ma, Xiang Dong Gao, Lei Yun, and Shu Qin Fu. "Data Fusion Algorithm for Asynchronous Radar Networks under Blanket Jamming." Applied Mechanics and Materials 157-158 (February 2012): 1446–52. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.1446.
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Owing to the incompleteness and asynchronicity of the observation data, it is hard for the asynchronous netted radar to track its target effectively under intense blanket jamming. This paper presents a kind of data fusion algorithm for the asynchronous sensors based on optimal linearization approach, providing a solution to the problem of target tracking of radar networks under blanket jamming. First, the optimal linearization processing technique of the observation equation is derived. Then, based on this, the state vector of the target is initially estimated in batch mode. Finally, the filtering is processed in sequence. The simulation results show that the data fusion algorithm presented in the paper can track the target in high accuracy.
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Plokhikh, Oleg. "Features of navigational radiosonde coordinate data processing for high resolution windfinding." ITM Web of Conferences 30 (2019): 03007. http://dx.doi.org/10.1051/itmconf/20193003007.
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Upper-air sounding systems (UASS) are the main means of obtaining aerological information to provide short-term and long-term weather forecasts, prevention of natural and anthropogenic catastrophes, etc. The UASS uses the principle of tracking a radiosonde launched into free flight, usually using a gas-filled balloon. Radiosondes are equipped with various sensors for measuring atmospheric parameters. The balloon, in addition to the means of the radiosonde delivery, serves as a horizontal wind sensor. At the end of the 20th century, theodolites and radars were used to track the radiosonde. In the 90s, such companies as Air, Vaisala, Graw, etc. developed UASSs using signals from the American Global Positioning System (GPS). These systems have fundamental advantages in terms of efficiency, size, mobility, radiosonde positioning accuracy and operation on mobile platforms. The use of Global Navigation Satellite System (GNSS) in upper-air sounding systems offer new perspectives of fine wind field measuring and detecting turbulent layers. The navigation radiosonde provides more detailed and high-quality information. The processing of such data has its own specificity in comparison with radar UASS. This paper discusses the coordinate data processing of a navigational radiosonde. To analyze the errors in estimating the wind speed, computer simulation of a balloon-sonde system is used. The coordinate data filter parameters and filtering efficiency was refined during the simulation.
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He, Jing, Bing Liu, and Yang Liu. "The Automatic Checkout Method of Balloon-Tracking Data at Unequal Intervals of Time." Applied Mechanics and Materials 444-445 (October 2013): 1644–48. http://dx.doi.org/10.4028/www.scientific.net/amm.444-445.1644.
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By tracking a beacon ball with theodolite and radar synchronously to inspect the accuracy of ra-dar data is one of the common calibrating methods without calibration towers at sea. Relied on some com-plications, the theodolite which acts as the standard in the precision test can not following the track of a d-ynamic target continuously for a long time. So the present processing methods based on isochronal interv-als can just make use of less continuous data. Upon that a new dynamic adaptive checkout method is introduced. It solves the problem of outliers-eliminating automatically among a great deal of data at unequal in-terval time by three culling steps. The results indicate that this method can eliminate outliers in beacon ball tracking data and make batch processing base on uncontinuous data implemented effectively. Not only the data quantity has been increased, but also the data process efficiency has been improved.
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Wang, Sun, Li, and Ding. "A New Multiple Hypothesis Tracker Integrated with Detection Processing." Sensors 19, no. 23 (November 30, 2019): 5278. http://dx.doi.org/10.3390/s19235278.
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In extant radar signal processing systems, detection and tracking are carried out independently, and detected measurements are utilized as inputs to the tracking procedure. Therefore, the tracking performance is highly associated with detection accuracy, and this performance may severely degrade when detections include a mass of false alarms and missed-targets errors, especially in dense clutter or closely-spaced trajectories scenarios. To deal with this issue, this paper proposes a novel method for integrating the multiple hypothesis tracker with detection processing. Specifically, the detector acquires an adaptive detection threshold from the output of the multiple hypothesis tracker algorithm, and then the obtained detection threshold is employed to compute the score function and sequential probability ratio test threshold for the data association and track estimation tasks. A comparative analysis of three tracking algorithms in a clutter dense scenario, including the proposed method, the multiple hypothesis tracker, and the global nearest neighbor algorithm, is conducted. Simulation results demonstrate that the proposed multiple hypothesis tracker integrated with detection processing method outperforms both the standard multiple hypothesis tracker algorithm and the global nearest neighbor algorithm in terms of tracking accuracy.
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Raboaca, Maria Simona, Catalin Dumitrescu, and Ioana Manta. "Aircraft Trajectory Tracking Using Radar Equipment with Fuzzy Logic Algorithm." Mathematics 8, no. 2 (February 6, 2020): 207. http://dx.doi.org/10.3390/math8020207.
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Radio-electronic means, including equipment for transmissions, radio-location, broadcasting, and navigation, allow the execution of various research missions and combat forces management. Determining the target coordinates and directing the armament towards them, obtaining and processing data about enemies, ensuring the navigation of ships, planes and outer atmospheric means, transmitting orders, decisions, reports and other necessary information for the armed forces; these are only some of the possibilities of radio-electronic technology. Fuzzy logic allows the linguistic description of the laws of command, operation and control of a system. When working with complex and nonlinear systems, it can often be observed that, as their complexity increases, there is a decrease in the significance of the details in describing the global behavior of the system. Even though such an approach may seem inadequate, it is often superior and less laborious than a rigorous mathematical approach. The main argument in favor of fuzzy set theory is to excel in operating with imprecise, vague notions. This article demonstrates the superiority of a fuzzy tracking system over the standard Kalman filter tracking system under the conditions of uneven accelerations and sudden change of direction of the targets, as well as in the case of failure to observe the target during successive scans. A cascading Kalman filtering algorithm was used to solve the speed ambiguity and to reduce the measurement error in real-time radar processing. The cascade filters are extended Kalman filters with controlled gain using fuzzy logic for tracking targets using radar equipment under difficult tracking conditions.
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Forlenza, Lidia, Giancarmine Fasano, Domenico Accardo, and Antonio Moccia. "Flight Performance Analysis of an Image Processing Algorithm for Integrated Sense-and-Avoid Systems." International Journal of Aerospace Engineering 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/542165.
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This paper is focused on the development and the flight performance analysis of an image-processing technique aimed at detecting flying obstacles in airborne panchromatic images. It was developed within the framework of a research project which aims at realizing a prototypical obstacle detection and identification System, characterized by a hierarchical multisensor configuration. This configuration comprises a radar, that is, the main sensor, and four electro-optical cameras. Cameras are used as auxiliary sensors to the radar, in order to increase intruder aircraft position measurement, in terms of accuracy and data rate. The paper thoroughly describes the selection and customization of the developed image-processing techniques in order to guarantee the best results in terms of detection range, missed detection rate, and false-alarm rate. Performance is evaluated on the basis of a large amount of images gathered during flight tests with an intruder aircraft. The improvement in terms of accuracy and data rate, compared with radar-only tracking, is quantitatively demonstrated.
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Lei, Yang, Alex Gardner, and Piyush Agram. "Autonomous Repeat Image Feature Tracking (autoRIFT) and Its Application for Tracking Ice Displacement." Remote Sensing 13, no. 4 (February 18, 2021): 749. http://dx.doi.org/10.3390/rs13040749.
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In this paper, we build on past efforts with regard to the implementation of an efficient feature tracking algorithm for the mass processing of satellite images. This generic open-source feature tracking routine can be applied to any type of imagery to measure sub-pixel displacements between images. The routine consists of a feature tracking module (autoRIFT) that enhances computational efficiency and a geocoding module (Geogrid) that mitigates problems found in existing geocoding algorithms. When applied to satellite imagery, autoRIFT can run on a grid in the native image coordinates (such as radar or map) and, when used in conjunction with the Geogrid module, on a user-defined grid in geographic Cartesian coordinates such as Universal Transverse Mercator or Polar Stereographic. To validate the efficiency and accuracy of this approach, we demonstrate its use for tracking ice motion by using ESA’s Sentinel-1A/B radar data (seven pairs) and NASA’s Landsat-8 optical data (seven pairs) collected over Greenland’s Jakobshavn Isbræ glacier in 2017. Feature-tracked velocity errors are characterized over stable surfaces, where the best Sentinel-1A/B pair with a 6 day separation has errors in X/Y of 12 m/year or 39 m/year, compared to 22 m/year or 31 m/year for Landsat-8 with a 16-day separation. Different error sources for radar and optical image pairs are investigated, where the seasonal variation and the error dependence on the temporal baseline are analyzed. Estimated velocities were compared with reference velocities derived from DLR’s TanDEM-X SAR/InSAR data over the fast-moving glacier outlet, where Sentinel-1 results agree within 4% compared to 3–7% for Landsat-8. A comprehensive apples-to-apples comparison is made with regard to runtime and accuracy between multiple implementations of the proposed routine and the widely-used “dense ampcor" program from NASA/JPL’s ISCE software. autoRIFT is shown to provide two orders of magnitude of runtime improvement with a 20% improvement in accuracy.
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Zhou, Yi, Tian Wang, Ronghua Hu, Hang Su, Yi Liu, Xiaoming Liu, Jidong Suo, and Hichem Snoussi. "Multiple Kernelized Correlation Filters (MKCF) for Extended Object Tracking Using X-Band Marine Radar Data." IEEE Transactions on Signal Processing 67, no. 14 (July 15, 2019): 3676–88. http://dx.doi.org/10.1109/tsp.2019.2917812.
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Sun, Hao, Ming Li, Lei Zuo, and Peng Zhang. "Resource Allocation for Multitarget Tracking and Data Reduction in Radar Network With Sensor Location Uncertainty." IEEE Transactions on Signal Processing 69 (2021): 4843–58. http://dx.doi.org/10.1109/tsp.2021.3101018.
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Huang, Qiong, Bing Heng Wu, Lu Gao, Dong Mei Guo, and Ming Lei Tong. "A Fast Target Searching and Capturing Method for Phased Array Radar." Advanced Materials Research 1037 (October 2014): 416–21. http://dx.doi.org/10.4028/www.scientific.net/amr.1037.416.
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Phased array radar (PAR) used for space exploration is a potential technique in many fields such as space target detection, tracking and orbit determination. Nevertheless, it may take a long time for PAR to detect fast-moving targets due to the large searching scope. This paper introduces the compressive sensing (CS) theory used in phased array tracking radar. A fast target searching method and angle-range imaging algorithm based on CS theory are presented, which can reduce the scanning time, sampling and processing data storage. The results of numerical simulation indicate that the proposed method using fewer scanning times can retain almost equal imaging and resolution quality compared to conventional method, which can also ensure the signal-to-noise ratio (SNR) of target detection.
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Nobis, Felix, Felix Fent, Johannes Betz, and Markus Lienkamp. "Kernel Point Convolution LSTM Networks for Radar Point Cloud Segmentation." Applied Sciences 11, no. 6 (March 15, 2021): 2599. http://dx.doi.org/10.3390/app11062599.
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State-of-the-art 3D object detection for autonomous driving is achieved by processing lidar sensor data with deep-learning methods. However, the detection quality of the state of the art is still far from enabling safe driving in all conditions. Additional sensor modalities need to be used to increase the confidence and robustness of the overall detection result. Researchers have recently explored radar data as an additional input source for universal 3D object detection. This paper proposes artificial neural network architectures to segment sparse radar point cloud data. Segmentation is an intermediate step towards radar object detection as a complementary concept to lidar object detection. Conceptually, we adapt Kernel Point Convolution (KPConv) layers for radar data. Additionally, we introduce a long short-term memory (LSTM) variant based on KPConv layers to make use of the information content in the time dimension of radar data. This is motivated by classical radar processing, where tracking of features over time is imperative to generate confident object proposals. We benchmark several variants of the network on the public nuScenes data set against a state-of-the-art pointnet-based approach. The performance of the networks is limited by the quality of the publicly available data. The radar data and radar-label quality is of great importance to the training and evaluation of machine learning models. Therefore, the advantages and disadvantages of the available data set, regarding its radar data, are discussed in detail. The need for a radar-focused data set for object detection is expressed. We assume that higher segmentation scores should be achievable with better-quality data for all models compared, and differences between the models should manifest more clearly. To facilitate research with additional radar data, the modular code for this research will be made available to the public.
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Mittermaier, Thomas J., Uwe Siart, Thomas F. Eibert, and Stefan Bonerz. "Extended Kalman Doppler tracking and model determination for multi-sensor short-range radar." Advances in Radio Science 14 (September 28, 2016): 39–46. http://dx.doi.org/10.5194/ars-14-39-2016.
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Abstract. A tracking solution for collision avoidance in industrial machine tools based on short-range millimeter-wave radar Doppler observations is presented. At the core of the tracking algorithm there is an Extended Kalman Filter (EKF) that provides dynamic estimation and localization in real-time. The underlying sensor platform consists of several homodyne continuous wave (CW) radar modules. Based on In-phase-Quadrature (IQ) processing and down-conversion, they provide only Doppler shift information about the observed target. Localization with Doppler shift estimates is a nonlinear problem that needs to be linearized before the linear KF can be applied. The accuracy of state estimation depends highly on the introduced linearization errors, the initialization and the models that represent the true physics as well as the stochastic properties. The important issue of filter consistency is addressed and an initialization procedure based on data fitting and maximum likelihood estimation is suggested. Models for both, measurement and process noise are developed. Tracking results from typical three-dimensional courses of movement at short distances in front of a multi-sensor radar platform are presented.
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Lantini, Livia, Fabio Tosti, Iraklis Giannakis, Lilong Zou, Andrea Benedetto, and Amir M. Alani. "An Enhanced Data Processing Framework for Mapping Tree Root Systems Using Ground Penetrating Radar." Remote Sensing 12, no. 20 (October 18, 2020): 3417. http://dx.doi.org/10.3390/rs12203417.
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The preservation of natural assets is nowadays an essential commitment. In this regard, root systems are endangered by fungal diseases which can undermine the health and stability of trees. Within this framework, ground penetrating radar (GPR) is emerging as a reliable non-destructive method for root investigation. A coherent GPR-based root-detection framework is presented in this paper. The proposed methodology is a multi-stage data analysis system that is applied to semi-circular measurements collected around the investigated tree. In the first step, the raw data are processed by applying several standard and advanced signal processing techniques in order to reduce noise-related information. In the second stage, the presence of any discontinuity element within the survey area is investigated by analysing the signal reflectivity. Then, a tracking algorithm aimed at identifying patterns compatible with tree roots is implemented. Finally, the mass density of roots is estimated by means of continuous functions in order to achieve a more realistic representation of the root paths and to identify their length in a continuous and more realistic domain. The method was validated in a case study in London (UK), where the root system of a real tree was surveyed using GPR and a soil test pit was excavated for validation purposes. Results support the feasibility of the data processing framework implemented in this study.
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Borovitsky, D. S., A. E. Zhesterev, V. P. Ipatov, and R. M. Mamchur. "Time Discriminator for Satellite Radar Altimeter Tracker System." Journal of the Russian Universities. Radioelectronics, no. 2 (June 5, 2018): 5–11. http://dx.doi.org/10.32603/1993-8985-2018-21-2-5-11.
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The article deals with the study of quasi-optimal TOA discriminator of an onboard echo-signal tracker of the altimeter carried by a space vehicle. In modern space-based altimeters, final data processing is imposed on the ground-based center receiving information from the spacecraft through a telemetry line, while the main task of an onboard delaylocked loop is to reliably retain the received echo-signal within the tracking window. The optimum discriminator of an onboard loop providing the potential accuracy of time measurement can appear difficult to implement. In the discriminator considered an error signal is proportional to the time mismatch between the half power point of the received power pattern and the tracking window. The equation for the equivalent time fluctuation variance is derived. It is also found that the discriminator proposed is as good at tracking precision as the maximum-power-point discriminator and maximums teepness discriminator, being at the same time much more attractive in terms of hardware complexity. The theoretical results are well consistent with the computer simulation. This simulation is performed both directly and using different methods of censoring the error signal at the discriminator output to effectively neutralize possible abnormal errors that are not taken into account by theoretical analysis.
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Biondi, Filippo, Angelica Tarpanelli, Pia Addabbo, Carmine Clemente, and Danilo Orlando. "Pixel Tracking to Estimate Rivers Water Flow Elevation Using Cosmo-SkyMed Synthetic Aperture Radar Data." Remote Sensing 11, no. 21 (November 2, 2019): 2574. http://dx.doi.org/10.3390/rs11212574.
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The lack of availability of historical and reliable river water level information is an issue that can be overcome through the exploitation of modern satellite remote sensing systems. This research has the objective of contributing in solving the information-gap problem of river flow monitoring through a synthetic aperture radar (SAR) signal processing technique that has the capability to perform water flow elevation estimation. This paper proposes the application of a new method for the design of a robust procedure to track over the time double-bounce reflections from bridges crossing rivers to measure the gap space existing between the river surface and bridges. Specifically, the difference in position between the single and double bounce is suitably measured over the time. Simulated and satellite temporal series of SAR data from COSMO-SkyMed data are compared to the ground measurements recorded for three gauges sites over the Po and Tiber Rivers, Italy. The obtained performance indices confirm the effectiveness of the method in the estimation of water level also in narrow or ungauged rivers.
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Zhiwei, Yang, He Shun, Liao Guisheng, and Ouyang Shan. "A Modified Fast Approximated Power Iteration Subspace Tracking Method for Space-Time Adaptive Processing." Journal of Electrical and Computer Engineering 2010 (2010): 1–6. http://dx.doi.org/10.1155/2010/973718.
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We propose a subspace-tracking-based space-time adaptive processing technique for airborne radar applications. By applying a modified approximated power iteration subspace tracing algorithm, the principal subspace in which the clutter-plus-interference reside is estimated. Therefore, the moving targets are detected by projecting the data on the minor subspace which is orthogonal to the principal subspace. The proposed approach overcomes the shortcomings of the existing methods and has satisfactory performance. Simulation results confirm that the performance improvement is achieved at very small secondary sample support, a feature that is particularly attractive for applications in heterogeneous environments.
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Cutajar, D., A. Magro, J. Borg, K. Z. Adami, G. Bianchi, G. Pupillo, A. Mattana, et al. "PyBIRALES: A Radar Data Processing Backend for the Real-Time Detection of Space Debris." Journal of Astronomical Instrumentation 09, no. 01 (February 26, 2020): 2050003. http://dx.doi.org/10.1142/s2251171720500038.
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The growing population of artificial satellites in near-Earth orbit has made the monitoring of orbital debris objects ever more important. Orbital debris objects pose a threat to these satellites as their orbit cannot be changed in order to avoid a collision. In recent years, the European Space Agency (ESA)’s Space Surveillance and Tracking (SST) programme has been assisting national institutions in the upgrading of their space debris detection and monitoring capabilities. One of the latest such systems within this programme is the BIRALES space surveillance system based in Italy. The receiving antenna is a radio telescope that is made up of 32 receivers which are placed on eight parabolic cylindrical reflectors of the North–South arm of the Istituto Nazionale di Astrofisica (INAF)’s Northern Cross. This work introduces a new software backend which was developed for this novel space debris sensor. The system was designed to be a fast, highly configurable software backend for the radio telescope’s acquisition and processing system and whose monitoring and control can be realized by a simple front-end web-based application. The real-time detection of Resident Space Object (RSO) is an important prerequisite for such a system as it gives the operator an immediate feedback loop on any detections whilst keeping the storage requirements at a minimum given that there is no need to save the raw data. The detection of high-velocity objects is achieved by means of a specially developed data processing pipeline that uses the received raw antenna voltages to generate a number of beams, collectively known as a multipixel, that cover the Field of View (FoV) of the instrument. The trajectory of the detected objects is determined by considering the illumination sequence within this multipixel. The initial results on known objects represent the first steps in extending the growing network of European SST systems.
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Chen, Gong, Wen Chong Xie, and Yong Liang Wang. "Angle Estimation with Knowledge-Aided Constraint-Based Space-Time Adaptive Monopulse." Advanced Materials Research 998-999 (July 2014): 966–70. http://dx.doi.org/10.4028/www.scientific.net/amr.998-999.966.
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The principle and cost analysis of Constraint-Based Space-Time Adaptive Monopulse (C-STAM) are given. Based on the idea of cognitive radar, a novel Knowledge-Aided Constraint-Based Space-Time Adaptive Monopulse (KA-C-STAM) is proposed. With the knowledge given by a tracking filter in data processing, the KA-C-STAM improves the performance of angle estimation. Numerical examples verify the validity of the novel method.
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Liu, D., R. Chen, B. Riedel, and W. Niemeier. "An improved approach to estimate large-gradient deformation using high resolution TerraSAR-X data." Solid Earth Discussions 6, no. 2 (September 17, 2014): 2759–78. http://dx.doi.org/10.5194/sed-6-2759-2014.
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Abstract. Interferometric Synthetic Aperture Radar (InSAR) has shown unique capabilities in numerous applications for deformation monitoring. However, InSAR will lose effectiveness with large-gradient deformation due to the limitation of maximum detectable phase gradient and the phase unwrapping step of InSAR. Coalfield is the exact object providing such challenges for InSAR technique. Strong mining activities often induces large scale non-linear deformation with large gradient. This paper integrates offset tracking technique based on Corner Reflector (CR) and InSAR to overcome relevant problems. By applying offset tracking to high resolution TerraSAR-X intensity images, the coarse estimation of large deformation was obtained and extracted, allowing the following InSAR processing to carry out phase unwrapping correctly. Finally, the fine estimation of deformation was done by the Persistent Scatterer InSAR (PSI) technique. The detected deformation time series indicated good root-mean-square errors (RMSE), validated by GPS in situ investigation. All InSAR data were processed in the open source software StaMPS and one in-house InSAR package.
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Bartsch, A., F. Fitzek, and R. H. Rasshofer. "Pedestrian recognition using automotive radar sensors." Advances in Radio Science 10 (September 18, 2012): 45–55. http://dx.doi.org/10.5194/ars-10-45-2012.
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Abstract. The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.
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Sun, Ke, Biyang Wen, and Ruokun Wang. "Analysis of Ship RCS Detected by Multifrequency HFGWR." International Journal of Antennas and Propagation 2017 (2017): 1–5. http://dx.doi.org/10.1155/2017/4964267.
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One of the important applications of high frequency-ground wave radar (HFGWR) is to detect offshore ships. A proper method should be used to obtain the ship radar cross section (RCS), which is a key parameter of the ship. This paper proposes a method based on an automatic information system (AIS). The relationship of the ship RCS versus bearing for different frequencies is analyzed by processing multifrequency HFGWR data. With this new method, bearing information is taken into consideration, which is not the case in traditional empirical formulas. The results provide prior knowledge for ship detection and tracking; therefore, the probability of detection is significantly improved.
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Hu, Xiu Hua, Lei Guo, and Hui Hui Li. "Adaptive Tracking Algorithm of Multi-Target Based on Fuzzy Clustering." Applied Mechanics and Materials 513-517 (February 2014): 448–52. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.448.
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For multi-target tracking system, aiming at solving the problem of low precision of state estimation caused by the data correlation ambiguity, the paper presents a novel multi-sensor multi-target adaptive tracking algorithm based on fuzzy clustering theory. Based on the joint probability data association algorithm, the new approach takes account of the case that whether the measure is validated and its possibility of belong to false alarm, and improves the correlation criterion of effective measurement with existing track on the basis of fuzzy clustering theory, which all perfect the update equation of target state estimation and the covariance. Meanwhile, with the adaptive distributed fusion processing structure, it enhance the robustness of the system and without prejudice to the real-time tracking. With the simulation case studies of radar/infrared sensor fusion multi-target tracking system, it verifies the effectiveness of the proposed approach.
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Zhou, Xueqin, Hong Ma, and Hang Xu. "An Experimental Multi-Target Tracking of AM Radio-Based Passive Bistatic Radar System via Multi-Static Doppler Shifts." Sensors 21, no. 18 (September 15, 2021): 6196. http://dx.doi.org/10.3390/s21186196.
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This paper presents a description of recent research and the multi-target tracking in experimental passive bistatic radar (PBR) system taking advantage of numerous non-cooperative AM radio signals via multi-static doppler shifts. However, it raises challenges for use by multiple spatially distributed AM radio illuminators for multi-target tracking in PBR system due to complex data association hypotheses and no directly used tracking algorithm in the practical scenario. To solve these problems, after a series of key array signal processing techniques in the self-developed system, by constructing a nonlinear measurement model, the novel method is proposed to accommodate nonlinear model by using the unscented transformation (UT) in Gaussian mixture (GM) implementation of iterated-corrector cardinality-balanced multi-target multi-Bernoulli (CBMeMBer). Simulation and experimental results analysis verify the feasibility of this approach used in a practical PBR system for moving multi-target tracking.
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Hou, Lili, and Qian Zhang. "Detection of Road Foreign Body Intrusion with Synthetic Aperture Radar." Mathematical Problems in Engineering 2020 (March 21, 2020): 1–7. http://dx.doi.org/10.1155/2020/9423925.
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Foreign body intrusion will cause interruption of road transportation and bring great threat to operation safety. Detection of foreign body intrusion is a key step for efficient recognition, location, and tracking of foreign body intrusion. Current detection approaches of foreign body intrusion are available, but can only detect in a certain range. As an active remote sensing technique, synthetic aperture radar (SAR) can monitor wide areas of the earth, and thus provides a viable way to detect road foreign body intrusion in a wide range. Firstly, because of large data, the SAR data in the azimuth is sparsely sampled to reduce data sampling. Then, before detection of foreign body intrusion, compressed sensing (CS) theory is utilized to reconstruct the sparsely sampled data. At last, Kalman filtering is adopted to detect foreign body intrusion. The simulated results and real data processing results both validate the proposed method.
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Yang, Xiaqing, Jun Shi, Yuanyuan Zhou, Chen Wang, Yao Hu, Xiaoling Zhang, and Shunjun Wei. "Ground Moving Target Tracking and Refocusing Using Shadow in Video-SAR." Remote Sensing 12, no. 18 (September 20, 2020): 3083. http://dx.doi.org/10.3390/rs12183083.
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Stable and efficient ground moving target tracking and refocusing is a hard task in synthetic aperture radar (SAR) data processing. Since shadows in video-SAR indicate the actual positions of moving targets at different moments without any displacement, shadow-based methods provide a new approach for ground moving target processing. This paper constructs a novel framework to refocus ground moving targets by using shadows in video-SAR. To this end, an automatic-registered SAR video is first obtained using the video-SAR back-projection (v-BP) algorithm. The shadows of multiple moving targets are then tracked using a learning-based tracker, and the moving targets are ultimately refocused via a proposed moving target back-projection (m-BP) algorithm. With this framework, we can perform detecting, tracking, imaging for multiple moving targets integratedly, which significantly improves the ability of moving-target surveillance for SAR systems. Furthermore, a detailed explanation of the shadow of a moving target is presented herein. We find that the shadow of ground moving targets is affected by a target’s size, radar pitch angle, carrier frequency, synthetic aperture time, etc. With an elaborate system design, we can obtain a clear shadow of moving targets even in X or C band. By numerical experiments, we find that a deep network, such as SiamFc, can easily track shadows and precisely estimate the trajectories that meet the accuracy requirement of the trajectories for m-BP.
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Haberlie, Alex M., and Walker S. Ashley. "A Method for Identifying Midlatitude Mesoscale Convective Systems in Radar Mosaics. Part II: Tracking." Journal of Applied Meteorology and Climatology 57, no. 7 (July 2018): 1599–621. http://dx.doi.org/10.1175/jamc-d-17-0294.1.
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AbstractThis research is Part II of a two-part study that evaluates the ability of image-processing and select machine-learning algorithms to detect, classify, and track midlatitude mesoscale convective systems (MCSs) in radar-reflectivity images for the conterminous United States. This paper focuses on the tracking portion of this framework. Tracking is completed through a two-step process using slice (snapshots of instantaneous MCS intensity) data generated in Part I. The first step is to perform spatiotemporal matching, which associates slices through temporally adjacent radar-reflectivity images to generate swaths, or storm tracks. When multiple slices are found to be matches, a difference-minimization procedure is used to associate the most similar slice with the existing swath. Once this step is completed, a second step combines swaths that are spatiotemporally close. Tracking performance is assessed by calculating select metrics for all available swath-building perturbations to determine the optimal approach in tracking. Frequency maps and time series generated from the swaths suggest that the spatiotemporal occurrence of these swaths is reasonable as determined from previous work. Further, these events exhibit a diurnal cycle that is distinct from that of overall convection for the conterminous United States. Last, machine-learning predictions are found to limit areas of high MCS frequency to the central and eastern Great Plains.
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Holleman, Iwan, Hans van Gasteren, and Willem Bouten. "Quality Assessment of Weather Radar Wind Profiles during Bird Migration." Journal of Atmospheric and Oceanic Technology 25, no. 12 (December 1, 2008): 2188–98. http://dx.doi.org/10.1175/2008jtecha1067.1.
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Abstract Wind profiles from an operational C-band Doppler radar have been combined with data from a bird tracking radar to assess the wind profile quality during bird migration. The weather radar wind profiles (WRWPs) are retrieved using the well-known volume velocity processing (VVP) technique. The X-band bird radar performed range–height scans perpendicular to the main migration direction and bird densities were deduced by counting and normalizing the observed echoes. It is found that the radial velocity standard deviation (σr) obtained from the VVP retrieval is a skillful indicator of bird migration. Using a threshold of 2 m s−1 on σr, more than 93% of the bird-contaminated wind vectors are rejected while over 70% of the true wind vectors are accepted correctly. For high bird migration densities the raw weather radar wind vectors have a positive speed bias of 8.6 ± 3.8 m s−1, while the quality-controlled wind vectors have a negligible speed bias. From the performance statistics against a limited area numerical weather prediction model, it is concluded that all (significant) bird contamination is removed and that high-quality weather radar wind profiles can be obtained, even during the bird migration season.
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Ishtiaq, Saima, Xiangrong Wang, and Shahid Hassan. "Multi-Target Tracking Algorithm Based on 2-D Velocity Measurements Using Dual-Frequency Interferometric Radar." Electronics 10, no. 16 (August 16, 2021): 1969. http://dx.doi.org/10.3390/electronics10161969.
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Multi-target tracking (MTT) generally requires either a network of Doppler radar receivers distributed at different locations or a phased array radar. The targets moving with small/no radial velocity or angular velocity only cannot be detected and localized completely by deploying Doppler radar without antenna arrays or multiple receivers. To resolve this issue, we present a new MTT algorithm based on 2-D velocity measurements, namely, radial and angular velocities, using dual-frequency interferometric radar. The contributions of the proposed research are twofold: First, we introduce the mathematical model and implementation of the proposed algorithm by explicitly establishing the relationship between 2-D velocity measurements and kinematic state of the target in terms of Cartesian coordinates. Based on 2-D velocity measurement function, the proposed MTT algorithm comprises the following steps: (i) data association using global nearest neighbor (GNN) method (ii) target state estimation using interacting multiple model (IMM) estimator combined with square-root cubature Kalman filter (SCKF) (iii) track management using rule-based M/N logic. Second, performance of the proposed algorithm is evaluated in terms of tracking accuracy, computational complexity and IMM mean model probabilities. Simulation results for different scenarios with multiple targets moving in different tracks have been presented to verify the effectiveness of the proposed algorithm.
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Li, Vincent Y. F., and Keith M. Miller. "Target Detection in Radar: Current Status and Future Possibilities." Journal of Navigation 50, no. 2 (May 1997): 303–13. http://dx.doi.org/10.1017/s0373463300023924.
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Most of the radar systems used in operating marine vessel traffic management services experience problems, such as track loss and track swap, which may cause confusion to the traffic regulators and lead to potential hazards in the harbour operation. The reason is mainly due to the limited adaptive capabilities of the algorithms used in the detection process. The decision on whether a target is present is usually based on the amplitude information of the returning echoes. Such method has a low efficiency in discriminating between the target and clutter, especially when the signal-to-noise ratio is low. With modern signal processing techniques more information can be extracted from the radar return signals and the tracking parameters of the previous scan. The objectives of this paper are to review the methods which are currently adopted in radar target identification, identify techniques for extracting additional information and consider means of data analysis for deciding the presence of a target. Instead of employing traditional two-state logic, it is suggested that the radar signal should be allocated in terms of threshold levels into fuzzy sets with its membership functions being related to the information extracted and the environment. Additional signal processing techniques are also suggested to explore pattern recognition aspects and discriminate features which are associated with a return signal from those of clutter.
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Filippo, Biondi. "COSMO-SkyMed Staring Spotlight SAR Data for Micro-Motion and Inclination Angle Estimation of Ships by Pixel Tracking and Convex Optimization." Remote Sensing 11, no. 7 (March 29, 2019): 766. http://dx.doi.org/10.3390/rs11070766.
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In past research, the problem of maritime targets detection and motion parameter estimation has been tackled. This new research aims to contribute by estimating the micro-motion of ships while they are anchored in port or stationed at the roadstead for logistic operations. The problem of motion detection of targets is solved using along-track interferometry (ATI) which is observed using two radars spatially distanced by a baseline extended in the azimuth direction. In the case of spaceborne missions, the performing of ATI requests using at least two real-time SAR observations spatially distanced by an along-track baseline. For spotlight spaceborne SAR re-synthesizing two ATI observations from one raw data is a problem because the received electromagnetic bursts are not oversampled for onboard memory space saving and data appears like a white random process. This problem makes appearing interlaced Doppler bands completely disjointed. This phenomenon, after the range-Doppler focusing process, causes decorrelation when considering the ATI interferometric phase information retransmitted by distributed targets. Only small and very coherent targets located within the same radar resolution cell are considered. This paper is proposing a new approach where the micro-motion estimation of ships, occupying thousands of pixels, is measured processing the information given by sub-pixel tracking generated during the coregistration process of two re-synthesized time-domain and partially overlapped sub-apertures generated splitting the raw data observed by a single wide Doppler band staring spotlight (ST) SAR map. The inclination of ships is calculated by low-rank plus sparse decomposition and Radon transform of some region of interest. Experiments are performed processing one set of COSMO-SkyMed ST SAR data.
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Celona, Sean, Sophia T. Merrifield, Tony de Paolo, Nate Kaslan, Tom Cook, Eric J. Terrill, and John A. Colosi. "Automated Detection, Classification, and Tracking of Internal Wave Signatures Using X-Band Radar in the Inner Shelf." Journal of Atmospheric and Oceanic Technology 38, no. 4 (April 2021): 789–803. http://dx.doi.org/10.1175/jtech-d-20-0129.1.
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AbstractA method based on machine learning and image processing techniques has been developed to track the surface expression of internal waves in near–real time. X-band radar scans are first preprocessed and averaged to suppress surface wave clutter and enhance the signal-to-noise ratio of persistent backscatter features driven by gradients in surface currents. A machine learning algorithm utilizing a support vector machine (SVM) model is then used to classify whether or not the image contains an internal solitary wave (ISW) or internal tide bore (bore). The use of machine learning is found to allow rapid assessment of the large dataset, and provides insight on characterizing optimal environmental conditions to allow for radar illumination and detection of ISWs and bores. Radon transforms and local maxima detections are used to locate these features within images that are determined to contain an ISW or bore. The resulting time series of locations is used to create a map of propagation speed and direction that captures the spatiotemporal variability of the ISW or bore in the coastal environment. This technique is applied to 2 months of data collected near Point Sal, California, and captures ISW and bore propagation speed and direction information that currently cannot be measured with instruments such as moorings and synthetic aperture radar (SAR).
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Fasano, Giancarmine, Domenico Accardo, Lidia Forlenza, Alfredo Renga, Giancarlo Rufino, Urbano Tancredi, and Antonio Moccia. "Real-Time Hardware-in-the-Loop Laboratory Testing for Multisensor Sense and Avoid Systems." International Journal of Aerospace Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/748751.
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This paper focuses on a hardware-in-the-loop facility aimed at real-time testing of architectures and algorithms of multisensor sense and avoid systems. It was developed within a research project aimed at flight demonstration of autonomous non-cooperative collision avoidance for Unmanned Aircraft Systems. In this framework, an optionally piloted Very Light Aircraft was used as experimental platform. The flight system is based on multiple-sensor data integration and it includes a Ka-band radar, four electro-optical sensors, and two dedicated processing units. The laboratory test system was developed with the primary aim of prototype validation before multi-sensor tracking and collision avoidance flight tests. System concept, hardware/software components, and operating modes are described in the paper. The facility has been built with a modular approach including both flight hardware and simulated systems and can work on the basis of experimentally tested or synthetically generated scenarios. Indeed, hybrid operating modes are also foreseen which enable performance assessment also in the case of alternative sensing architectures and flight scenarios that are hardly reproducible during flight tests. Real-time multisensor tracking results based on flight data are reported, which demonstrate reliability of the laboratory simulation while also showing the effectiveness of radar/electro-optical fusion in a non-cooperative collision avoidance architecture.
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Perna, Stefano, Francesco Soldovieri, and Moeness Amin. "Editorial for Special Issue “Radar Imaging in Challenging Scenarios from Smart and Flexible Platforms”." Remote Sensing 12, no. 8 (April 17, 2020): 1272. http://dx.doi.org/10.3390/rs12081272.
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Microwave radar imaging plays a key role in several civilian and defense applications, such as security, surveillance, diagnostics and monitoring in civil engineering and cultural heritage, environment observation, with particular emphasis on disasters and crisis management, where it is required to remotely sense the area of interest in a timely, safe and effective way. To address these constraints, a technological opportunity is offered by radar systems mounted onboard smart and flexible platforms, such as ground-based ones, airplanes, helicopters, drones, unmanned aerial and ground vehicles (UAV and UGV). For this reason, radar imaging based on data collected by such platforms is gaining interest in the remote sensing community. However, a full exploitation of smart and flexible radar systems requires the development and use of image formation techniques and reconstruction approaches able to exploit and properly deal with non-conventional data acquisition configurations. The other main issue is related to the need to operate in challenging environments, and still deliver high target detection, localization and tracking. These environments include through the wall imaging, rugged terrain and rough surface/subsurface. In these cases, one seeks mitigation of the adverse effects of clutter and multipath via the implementation of effective signal processing strategies and electromagnetic modeling.
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Donati, Davide, Bernhard Rabus, Jeanine Engelbrecht, Doug Stead, John Clague, and Mirko Francioni. "A Robust SAR Speckle Tracking Workflow for Measuring and Interpreting the 3D Surface Displacement of Landslides." Remote Sensing 13, no. 15 (August 3, 2021): 3048. http://dx.doi.org/10.3390/rs13153048.
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We present a workflow for investigating large, slow-moving landslides which combines the synthetic aperture radar (SAR) technique, GIS post-processing, and airborne laser scanning (ALS), and apply it to Fels landslide in Alaska, US. First, we exploit a speckle tracking (ST) approach to derive the easting, northing, and vertical components of the displacement vectors across the rock slope for two five-year windows, 2010–2015 and 2015–2020. Then, we perform post-processing in a GIS environment to derive displacement magnitude, trend, and plunge maps of the landslide area. Finally, we compare the ST-derived displacement data with structural lineament maps and profiles extracted from the ALS dataset. Relying on remotely sensed data, we estimate that the thickness of the slide mass is more than 100 m and displacements occur through a combination of slumping at the toe and planar sliding in the central and upper slope. Our approach provides information and interpretations that can assist in optimizing and planning fieldwork activities and site investigations at landslides in remote locations.
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Tsai, Tianyi, Zhiqiang Liao, Zhiquan Ding, Yuan Zhao, and Bin Tang. "Detection of Unresolved Targets for Wideband Monopulse Radar." Sensors 19, no. 5 (March 3, 2019): 1084. http://dx.doi.org/10.3390/s19051084.
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Detecting unresolved targets is very important for radars in their target tracking phase. For wideband radars, the unresolved target detection algorithm should be fast and adaptive to different bandwidths. To meet the requirements, a detection algorithm for wideband monopulse radars is proposed, which can detect unresolved targets for each range profile sampling points. The algorithm introduces the Gaussian mixture model and uses a priori information to achieve high performance while keeping a low computational load, adaptive to different bandwidths. A comparison between the proposed algorithm and the latest unresolved target detection algorithm Joint Multiple Bin Processing Generalized Likelihood Ratio Test (JMBP GLRT) is carried out by simulation. On Rayleigh distributed echoes, the detection probability of the proposed algorithm is at most 0.5456 higher than the JMBP GLRT for different signal-to-noise ratios (SNRs), while the computation time of the proposed algorithm is no more than two 10,000ths of the JMBP GLRT computation time. On bimodal distributed echoes, the detection probability of the proposed algorithm is at most 0.7933 higher than the JMBP GLRT for different angular separations of two unresolved targets, while the computation time of the proposed algorithm is no more than one 10,000th of the JMBP GLRT computation time. To evaluate the performance of the proposed algorithm in a real wideband radar, an experiment on field test measured data was carried out, in which the proposed algorithm was compared with Blair GLRT. The results show that the proposed algorithm produces a higher detection probability and lower false alarm rate, and completes detections on a range profile within 0.22 ms.