A Probability Hypothesis Density Filter and Data Association Based Algorithm for Multitarget Tracking with Pulse Doppler Radar
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摘要: 为了解决杂波环境下脉冲多普勒(PD)雷达的多目标跟踪问题，提出一种距离模糊情况下基于概率假设密度滤波(PHDF)和数据关联(DA)的联合解距离模糊和多目标跟踪方法。该方法使雷达采用一组脉冲重复频率(PRF)交替变换的工作模式，并对雷达生成的模糊量测进行多假设，得到扩展量测集；然后，利用PHDF可以有效滤除杂波和避免目标-量测数据关联的突出优点，对扩展量测集进行滤波，得到粗略的目标状态估计；最后，对PHDF的滤波结果进行航迹-估计值关联，给出多目标航迹信息。仿真结果表明，该算法可以同时给出目标个数和各目标状态估计，实现杂波环境和距离模糊条件下对多目标的有效跟踪。
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关键词:
- 多目标跟踪 /
- 概率假设密度滤波(PHDF) /
- 距离模糊 /
- 粒子滤波 /
- 脉冲重复频率(PRF)
Abstract: To solve the problem of multitarget tracking with the Pulse Doppler (PD) radar in clutters, a novel method based on Probability Hypothesis Density Filter (PHDF) and Data Association (DA) for joint range ambiguity resolving and multitarget tracking with range ambiguity is proposed. The method sets the radar work with a set of Pulse Repetition Frequencies (PRFs) alternately, and obtains the extended measurements set by making multiple hypotheses with the ambiguous measurement generated by the radar. Then, filters with extended measurement set with the PHDF by making full use of the advantages of which that it can eliminate clutters effectively and avoid the association between target and measurement. Finally it implements a track-estimate data association with the outputs of the PHDF and provides target tracks. Simulation results demonstrate that the proposed method can estimate the number of target as well as individual target state, and succeeds in multitarget tracking with range ambiguity in clutters. -
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