FUZZY-CONTROL-BASED PARTICLE FILTER FOR MANEUVERING TARGET TRACKING
FUZZY-CONTROL-BASED PARTICLE FILTER FOR MANEUVERING TARGET TRACKING
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DOI：
10.2528/pier11051907
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发表时间：
2011
影响因子：
6.7
通讯作者：
Xianfeng Wang;Junfeng Chen;Zhiguo Shi;K. Chen
中科院分区：
文献类型：
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作者：
Xianfeng Wang;Junfeng Chen;Zhiguo Shi;K. Chen
结合标准粒子滤波(SPF)和多模型粒子滤波(MMPF)的优点，提出了一种新的基于模糊控制的粒子滤波算法(FCPF)用于机动目标跟踪。也就是说，在非机动运动中采用SPF，而在机动运动中采用MMPF。FCPF的关键是利用一个在一定程度上模仿人类思维的模糊控制器来检测目标的机动，并使用反向校正子算法来缓解MMPF由于检测延迟而导致的性能下降。仿真结果表明，该算法在保持基本相同的计算复杂度的情况下，具有比SPF算法更高的跟踪精度。与MMPF相比，两种算法都没有跟踪损失，但FCPF的跟踪精度略好于MMPF，并且FCPF的计算时间约为MMPF的66%。因此，该算法为机动目标跟踪提供了一种更有效的方法。
In this paper, we propose a novel fuzzy-control-based particle fllter (FCPF) for maneuvering target tracking, which combines the advantages of standard particle fllter (SPF) and multiple model particle fllter (MMPF). That is, the SPF is adopted during non-maneuvering movement while the MMPF is adopted during maneuvering movement. The key point of the FCPF is to use a fuzzy controller, which could imitate the thoughts of human beings in some degree, to detect the target's maneuver and use a backward correction sub-algorithm to alleviate the performance degradation of MMPF caused by detection delay. Simulation results indicate that the proposed algorithm has a much better tracking accuracy than the SPF while keeps approximately equal computational complexity. Compared with MMPF, both algorithms have no tracking lost, but the tracking accuracy of the proposed FCPF is a little better than the MMPF, and the FCPF consumes about 66% computation time of the MMPF. Thus, the proposed algorithm ofiers a more efiective way for maneuvering target tracking.