Relevant bibliographies by topics / Tracking radar

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

Academic literature on the topic 'Tracking radar'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 June 2025

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Journal articles on the topic "Tracking radar"

1

Tian, Shu Rong, Xiao Shu Sun, and Xi Jing Sun. "PHD Filter for Multi-Radar Multi-Target Tracking." Advanced Materials Research 734-737 (August 2013): 2730–33. http://dx.doi.org/10.4028/www.scientific.net/amr.734-737.2730.

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Target tracking with multiple radars is more efficient than tracking with one radar. In this paper, a multi-radar tracking system is proposed even when targets are occluded at radars. Observations from all radars are composed, then, Probability Hypothesis Density (PHD) filter is used to estimate the multi-target state and the number at each time step. PHD particle filter implementation is used to perform the proposed method consisting of multiple mameuvering targets.
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Zhang, Gangsheng, Junwei Xie, Haowei Zhang, Weike Feng, Mingjie Liu, and Cong Qin. "Power Allocation Scheme for Multi-Static Radar to Stably Track Self-Defense Jammers." Remote Sensing 16, no. 15 (2024): 2699. http://dx.doi.org/10.3390/rs16152699.

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Due to suppression jamming by jammers, the signal-to-interference-plus-noise ratio (SINR) during tracking tasks is significantly reduced, thereby decreasing the target detection probability of radar systems. This may result in the interruption of the target track. To address this issue, we propose a multi-static radar power allocation algorithm that enhances the detection and tracking performance of multiple radars in relation to their targets by optimizing power resource allocation. Initially, the echo signal model and measurement model of multi-static radar are formulated, followed by the de
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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
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Zhang, Zhenkai, Bing Zhang, Zhibin Xie, and Yi Yang. "Radar Selection Method Based on an Improved Information Filter in the LPI Radar Network." International Journal of Antennas and Propagation 2018 (December 17, 2018): 1–6. http://dx.doi.org/10.1155/2018/6104849.

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In order to save the radar resources and obtain the better low probability intercept ability in the network, a novel radar selection method for target tracking based on improved interacting multiple model information filtering (IMM-IF) is presented. Firstly, the relationship model between radar resource and tracking accuracy is built, and the IMM-IF method is presented. Then, the information gain of every radar is predicted according to the IMM-IF, and the radars with larger information gain are selected to track target. Finally, the weight parameters for the tracking fusion are designed after
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Zhang, Yuanshi, Minghai Pan, and Qinghua Han. "Joint Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking of Unmanned Cluster Based on Fuzzy Logic Reasoning." Sensors 20, no. 5 (2020): 1371. http://dx.doi.org/10.3390/s20051371.

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The unmanned aerial vehicle (UAV) cluster is gradually attracting more attention, which takes advantage over a traditional single manned platform. Because the size of the UAV platform limits the transmitting power of its own radar, how to reduce the transmitting power while meeting the detection accuracy is necessary. Aim at multiple-target tracking (MTT), a joint radar node selection and power allocation algorithm for radar networks is proposed. The algorithm first uses fuzzy logic reasoning (FLR) to obtain the priority of targets to radars, and designs a radar clustering algorithm based on t
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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 (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 t
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Hussein, Mahmoud Yahia. "Target Tracking Radar." IOSR Journal of Engineering 4, no. 5 (2014): 23–28. http://dx.doi.org/10.9790/3021-04512328.

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Klare, Jens, Florian Behner, Claudio Carloni, et al. "The Future of Radar Space Observation in Europe—Major Upgrade of the Tracking and Imaging Radar (TIRA)." Remote Sensing 16, no. 22 (2024): 4197. http://dx.doi.org/10.3390/rs16224197.

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The use of near-Earth space has grown dramatically during the last decades, resulting in thousands of active and inactive satellites and a huge amount of space debris. To observe and monitor the near-Earth space environment, radar systems play a major role as they can be operated at any time and under any weather conditions. The Tracking and Imaging Radar (TIRA) is one of the largest space observation radars in the world. It consists of a 34m Cassegrain antenna, a precise tracking radar, and a high-resolution imaging radar. Since the 1990s, TIRA contributes to the field of space domain awarene
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Revenko, V. Yu. "RADAR CHARACTERISTICS OF PRECIPITATION AFFECTING THE TRACKING OF SHIP’S RADAR OBJECTS." Shipping & Navigation 33, no. 1 (2022): 106–10. http://dx.doi.org/10.31653/2306-5761.33.2022.106-110.

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In this paper, we consider the possibility of using the radar characteristics under precipitation conditions in order to reduce the echo signal’s negative impact on the object tracking performed by the ship’s radar. Precipitation particles’ size, state (solid or liquid phase), shape, and the factors that determine their combined action play an important role in echo signal formation. The rain particles’ size in comparison with the wavelength of the ship’s radar may contribute to the creation of a larger or smaller noise echo signal on the ship’s radar display. This signal’s power in the Raylei
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Zhao, Yong, and HongBing Fang. "Phased-Array Radar Array Signals Processing for Detecting, Inverse Synthetic Aperture Radar Imaging and Tracking Integration." Journal of Physics: Conference Series 2999, no. 1 (2025): 012053. https://doi.org/10.1088/1742-6596/2999/1/012053.

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Abstract Phased array radars are progressively replacing traditional radars to meet modern military requirements, particularly in target detection. The versatility of phased array radar enables the accomplishment of a broader range of functions through the application of diverse processing techniques. To achieve faster response speeds and gather more comprehensive target information during radar detection, we propose, for the first time, an integrated design for phased array radar that combines target detection, target inverse synthetic aperture imaging and trajectory tracking design based on
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Dissertations / Theses on the topic "Tracking radar"

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Chin, Yue Hann. "Radar tracking system development." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/30368.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (leaf 65).<br>The Airborne Seeker Test Bed (ASTB) is an airborne sensor testing platform operated by the Tactical Defense Systems group at MIT Lincoln Laboratory. The Instrumentation Head (IH) is a primary sensor on the ASTB. It is a passive X-band radar receiver located on the nose of the pla
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Nagarajan, Nishatha. "Target Tracking Via Marine Radar." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1345125374.

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Southcott, Michael L. "Radar track association /." Title page, table of contents and abstract only, 1998. http://web4.library.adelaide.edu.au/theses/09PH/09phs726.pdf.

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Raghavan, V. P. "High precision laser radar tracking device /." Online version of thesis, 1991. http://hdl.handle.net/1850/11453.

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Tam, Wing Ip. "Tracking filters for radar systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ28884.pdf.

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Sahin, Mehmet Alper. "Performance Optimization Of Monopulse Tracking Radar." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12605364/index.pdf.

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An analysis and simulation tool is developed for optimizing system parameters of the monopulse target tracking radar and observing effects of the system parameters on the performance of the system over different scenarios. A monopulse tracking radar is modeled for measuring the performance of the radar with given parameters, during the thesis studies. The radar model simulates the operation of a Class IA type monopulse automatic tracking radar, which uses a planar phased array. The interacting multiple model (IMM) estimator with the Probabilistic Data Association (PDA) technique is used as the
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Miller, Samuel(Samuel John). "Object tracking in mmWave radar networks." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127079.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, May, 2020<br>Cataloged from the official PDF of thesis.<br>Includes bibliographical references (pages 71-87).<br>Location-aware devices enable new services such as localization and tracking of objects within existing wireless communication networks like cellular mobile, Wi-Fi, and radio. To ensure these services are also available in the evolving millimeter wave (mmWave) communication infrastructure, it is important to develop algorithms that enable mmWave devices, like radars and 5G nodes, to loca
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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.<br>"December 1996." Thesis advisor(s): Gurnam S. Gill. Includes bibliographical references (p. 45). Also available online.
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De, Villiers Hendrik Barney. "Correlation and tracking using multiple radar sensors /." Link to the online version, 2006. http://hdl.handle.net/10019/1006.

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Svanström, Fredrik. "Kalman filtering : With a radar tracking implementation." Thesis, Linnéuniversitetet, Institutionen för matematik (MA), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-30855.

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The Kalman filter algorithm can be applied as a recursive estimator of the state of a dynamic system described by a linear difference equation. Given discrete measurements linearly related to the state of the system, but corrupted by white Gaussian noise, the Kalman filter estimate of the system is statistically optimal with respect to a quadratic function of the estimate error. The first objective of this paper is to give deep enough insight into the mathematics of the Kalman filter algorithm to be able to choose the correct type of algorithm and to set all the parameters correctly in a basic
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Books on the topic "Tracking radar"

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Biernson, George. Optimal radar tracking systems. Wiley, 1990.

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Tam, Wing Ip. Tracking filters for radar systems. National Library of Canada = Bibliothèque nationale du Canada, 1999.

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3

Oskar, Blumtritt, Petzold Hartmut, and Aspray William, eds. Tracking the history of radar. IEEE-Rudgers Center for the History of Electrical Engineering, 1994.

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Yaakov, Bar-Shalom, and University of California, Los Angeles. University Extension., eds. Multitarget-multisensor tracking: Applications and advances. Artech House, 1990.

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Griffiths, Hugh. An introduction to passive radar. 2nd ed. Artech House, 2022.

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IEE Professional Network on Concepts for Automation & Control. International seminar: Target tracking, algorithms & applications : Tuesday, 16 October-Wednesday, 17 October 2001 : Conferentiehotel Drienerburght, University of Twente, Enschede, The Netherlands. Thales, 2001.

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Kolawole, Michael. Radar systems, peak detection and tracking. Butterworth-Heinemann, 2003.

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Elshaktori, Muwaffag. The circular monopulse tracking radar system. University of Birmingham, 1988.

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Bogler, Philip L. Radar principles with applications to tracking systems. Wiley, 1990.

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Center, Lewis Research, ed. Digital tracking loops for a programmable digital modem. Lewis Research Center, National Aeronautics and Space Administration, 1992.

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Book chapters on the topic "Tracking radar"

1

Winton, Scott C. "Radar Tracking." In Handbook of Radar Signal Analysis. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781315161402-13.

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Bruder, Joseph A. "Range Tracking." In Principles of Modern Radar. Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1971-9_17.

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Ewell, George W., and Neal T. Alexander. "Angle Tracking." In Principles of Modern Radar. Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1971-9_18.

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Rahman, Habibur. "Tracking Radars." In Fundamental Principles of Radar. CRC Press, 2019. http://dx.doi.org/10.1201/9780429279478-10.

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Haykin, Simon. "Cognitive Radar." In Knowledge-Based Radar Detection, Tracking, and Classification. John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470283158.ch2.

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

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Benavoli, Alessio, Luigi Chisci, Alfonso Farina, Sandro Immediata, and Luca Timmoneri. "Knowledge-Based Radar Tracking." In Knowledge-Based Radar Detection, Tracking, and Classification. John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470283158.ch8.

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Toomay, J. C. "Detection Tracking." In Radar Principles for the Non-Specialist. Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-011-6985-1_3.

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Mahafza, Bassem R. "Target Tracking." In Radar Systems Analysis and Design Using MATLAB®, 4th ed. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003051282-17.

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Patterson, Douglas M., and Richard A. Ashley. "Glint Tracking Errors in Radar." In Dynamic Modeling and Econometrics in Economics and Finance. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4419-8688-7_7.

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Conference papers on the topic "Tracking radar"

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Gigleux, Benjamin, François Vincent, and Eric Chaumette. "Covariance Estimation of Generalized Monopulse for Radar Tracking." In 2024 International Radar Conference (RADAR). IEEE, 2024. https://doi.org/10.1109/radar58436.2024.10994171.

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Saïdane, J., C. Morisseau, D. Bourgeois, and M. Flécheux. "Highly Maneuvering Target Tracking with a Transformer Network." In 2024 International Radar Conference (RADAR). IEEE, 2024. https://doi.org/10.1109/radar58436.2024.10993550.

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Dell, Martin, Wolfgang Bradfisch, Steffen Schober, and Clemens Klöck. "RadarMOTR: Multi-Object Tracking with Transformers on Range-Doppler Maps." In 2024 International Radar Conference (RADAR). IEEE, 2024. https://doi.org/10.1109/radar58436.2024.10994166.

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Andres, Salvador, Jorge Lanzuela, Andres Ocabo, et al. "FMCW Radar system for UAV tracking and identification by MDS recognition." In 2024 International Radar Conference (RADAR). IEEE, 2024. https://doi.org/10.1109/radar58436.2024.10994094.

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de Rochechouart, Maxence, Amal El Fallah Seghrouchni, Frederic Barbaresco, and Raed Abu Zitar. "Radar/Optro Meta-sensor: Augmented Radar Tracking Performances by Adaptive Camera Resources Allocation." In 2024 International Radar Conference (RADAR). IEEE, 2024. https://doi.org/10.1109/radar58436.2024.10993879.

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Ristic, Branko, and Marcel L. Hernandez. "Tracking systems." In 2008 IEEE Radar Conference (RADAR). IEEE, 2008. http://dx.doi.org/10.1109/radar.2008.4721153.

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Attal, Yoann, Laurent Savy, Ludovic Grivault, and Laurent Ratton. "LPI target tracking involving IEKF." In 2019 International Radar Conference (RADAR). IEEE, 2019. http://dx.doi.org/10.1109/radar41533.2019.171315.

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De Rauw, Dominique, and Christian Barbier. "Spectral coherence applied to vessel tracking." In 2014 International Radar Conference (Radar). IEEE, 2014. http://dx.doi.org/10.1109/radar.2014.7060291.

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Walton, A. M. "Space based radar tracking filter." In IEE Colloquium on `Algorithms for Target Tracking'. IEE, 1995. http://dx.doi.org/10.1049/ic:19950675.

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Ahmeda, S. S. "Tracking multiple targets with a phased array radar." In Radar Systems (RADAR 97). IEE, 1997. http://dx.doi.org/10.1049/cp:19971745.

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Reports on the topic "Tracking radar"

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Chong, Edwin, and Louis L. Scharf. Integrated Radar Imaging, Target Tracking and Sensor Scheduling. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada448056.

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Lehman, Sean K. Volume Imaging & Tracking Radar Open Research Topics. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1634296.

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Doan, Larry, Patrick A. Day, and Oleg Brovko. Large Dynamic Range Radar Cross Section Parallel Tracking. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada304014.

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Kabela, Erik D., S. Craig Moss, Daniel B. Koch, et al. Feasibility of Using Radar for Characterizing and Tracking Plumes. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1436044.

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Lambert, H. C., S. R. Vogel, A. S. Brewster, and K. Dunn. Validating the Modeling and Simulation of a Generic Tracking Radar. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada502982.

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Lawton, John A., Robert J. Jesionowski, and Paul Zarchan. Comparison of Four Filtering Options for a Radar Tracking Problem,. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada329021.

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Bizup, David. A Centripetal Acceleration Statistic for Tracking Maneuvering Targets with Radar. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada467466.

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Burrows, M. L. Two-Dimensional ESPRIT with Tracking for Radar Imaging and Feature Extraction. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada405754.

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Cottrill, Stanley D. Tracking Radar Advanced Signal Processing and Computing for Kwajalein Atoll (KA) Application. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada259066.

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Borden, Brett. What is the Radar Tracking 'Glint' Problem and Can It Be Solved. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada266509.

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