Conventional multitarget tracking systems presume that each target can produce at most one measurement per scan. Due to the multiple ionospheric propagation paths in over-the-horizon radar (OTHR), this assumption is not valid. To solve this problem, this paper proposes a novel tracking algorithm based on the theory of finite set statistics (FISST) called the multipath probability hypothesis density (MP-PHD) filter in cluttered environments. First, the FISST is used to derive the update equation, and then Gaussian mixture (GM) is introduced to derive the closed-form solution of the MP-PHD filter. Moreover, the extended Kalman filter (EKF) is presented to deal with the nonlinear problem of the measurement model in OTHR. Eventually, the simulation results are provided to demonstrate the effectiveness of the proposed filter.

Filename	Size	Update
GM-PHD1\extendedTargetPHDfilter.m.htm	6798	2019-02-28
GM-PHD1\extendedTargetTrackingPHD.m.htm	6275	2019-02-28
GM-PHD1\generateClutter.m.htm	1027	2019-02-28
GM-PHD1\generateExtendedMeasurements.m.htm	1490	2019-02-28
GM-PHD1\GM_PHD1.m__.htm	4424	2019-02-28
GM-PHD1\initParameters_project.m.htm	1699	2019-02-28
GM-PHD1\partitionMeasurementSet_4.m.htm	5400	2019-02-28
GM-PHD1\phdFilter.m.htm	4332	2019-02-28
GM-PHD1\phdPruning.m__.htm	1764	2019-02-28
GM-PHD1\phdStateExtraction.m__.htm	811	2019-02-28
GM-PHD1\PHD_MTT.m__.htm	16286	2019-02-28
GM-PHD1\plotPHDsurface.m__.htm	1507	2019-02-28
GM-PHD1\readme.m__.htm	1406	2019-02-28
GM-PHD1\Sigmacircle.m__.htm	778	2019-02-28
GM-PHD1	0	2019-02-28

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