DA-PMHT for Multistatic Passive Radar Multitarget Tracking in Dense Clutter Environment
Multistatic passive radar exploits illuminators of opportunity such as radio or television stations for tracking airborne targets. This paper focuses on broadcast signals in a single frequency network modulated according to the digital audio/video broadcasting (DAB/DVB) standards. The main challenge...
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| Vydané v: | IEEE access Ročník 7; s. 49316 - 49326 |
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| Médium: | Journal Article |
| Jazyk: | English |
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2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 2169-3536, 2169-3536 |
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| Abstract | Multistatic passive radar exploits illuminators of opportunity such as radio or television stations for tracking airborne targets. This paper focuses on broadcast signals in a single frequency network modulated according to the digital audio/video broadcasting (DAB/DVB) standards. The main challenge is that one has to solve the measurement-to-illuminator association ambiguity in addition to the conventional measurement-to-target association ambiguity, which increases data association complexity greatly. In this paper, to solve the additional measurement-to-illuminator data association ambiguity, a novel deterministic annealing probabilistic multi-hypothesis tracker based on the extended Kalman filter is proposed. The proposed algorithm works directly in the original three-dimensional Cartesian space, and can efficiently handle a large number of association hypotheses among the targets, measurements, and illuminators in a natural way, also it is computationally attractive. As the angular measurement is not available or often of extremely poor quality, this paper assumes measurements of bistatic range and range rate and does not process bearing information. The simulation results show that the proposed algorithm works reasonably well in dense clutter environment for multistatic passive radar system. |
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| AbstractList | Multistatic passive radar exploits illuminators of opportunity such as radio or television stations for tracking airborne targets. This paper focuses on broadcast signals in a single frequency network modulated according to the digital audio/video broadcasting (DAB/DVB) standards. The main challenge is that one has to solve the measurement-to-illuminator association ambiguity in addition to the conventional measurement-to-target association ambiguity, which increases data association complexity greatly. In this paper, to solve the additional measurement-to-illuminator data association ambiguity, a novel deterministic annealing probabilistic multi-hypothesis tracker based on the extended Kalman filter is proposed. The proposed algorithm works directly in the original three-dimensional Cartesian space, and can efficiently handle a large number of association hypotheses among the targets, measurements, and illuminators in a natural way, also it is computationally attractive. As the angular measurement is not available or often of extremely poor quality, this paper assumes measurements of bistatic range and range rate and does not process bearing information. The simulation results show that the proposed algorithm works reasonably well in dense clutter environment for multistatic passive radar system. |
| Author | Wei, Wei Lu, Xiaofeng Li, Xiaohua Zhao, Chenxu |
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| References | ref13 ref15 pikora (ref11) 2013 ref10 streit (ref22) 1995 ref2 ref1 ref16 crouse (ref25) 2009; 4 ref19 ref18 malanowski (ref17) 2009 ref24 bar-shalom (ref20) 1995 ref23 ref26 li (ref12) 2014 ref27 choi (ref21) 2014; 9 daun (ref14) 2008 ref8 ref7 ref9 ref4 ref3 ref6 ref5 |
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| SubjectTerms | Algorithms Ambiguity Cartesian coordinates Clutter data association deterministic annealing Extended Kalman filter Hypotheses Illuminators Multiple target tracking Multistatic passive radar Passive radar probabilistic multi-hypothesis tracker Radar equipment Radar tracking Receivers Target tracking Television stations Time measurement |
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| Title | DA-PMHT for Multistatic Passive Radar Multitarget Tracking in Dense Clutter Environment |
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