TRACKING AIRBORNE TARGETS HIDDEN IN BLIND DOPPLER USING CURRENT STATISTICAL MODEL PARTICLE FILTER
TRACKING AIRBORNE TARGETS HIDDEN IN BLIND DOPPLER USING CURRENT STATISTICAL MODEL PARTICLE FILTER
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DOI：
10.2528/pier08012407
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发表时间：
2008
影响因子：
6.7
通讯作者：
Zhiguo Shi;Shaohua Hong;K. Chen
中科院分区：
文献类型：
--
作者：
Zhiguo Shi;Shaohua Hong;K. Chen
本文旨在寻找一种估计性能好、易于硬件实现的盲多普勒雷达机载目标跟踪算法。针对当前统计模型对盲多普勒效应引起的机动运动的有效性，提出了一种基于当前统计模型的粒子滤波器（CSM-PF），用于盲多普勒效应下的机载目标跟踪。仿真结果表明，CSM-PF在跟踪精度和跟踪连续性方面与交互式多模型粒子滤波（IMM-PF）具有相似的性能，但避免了机动目标模型选择的困难。此外，当考虑硬件实现时，所提出的CSM-PF具有更低的处理延迟，更少的资源利用率和更低的硬件复杂度比IMM-PF。
This paper aims at finding an algorithm featuring good estimation performance and easy hardware implementation for tracking airborne target hidden in blind Doppler. Incorporating the current statistical model which is effective in dealing with the maneuvering motions that most blind Doppler issues are caused, a current statistical model particle filter (CSM-PF) is presented in this paper for tracking airborne targets hidden in blind Doppler. Simulation results demonstrate that the proposed CSM-PF shows similar performance with the interacting multiple model particle filter (IMM-PF) in terms of tracking accuracy and track continuity, but it avoids the difficulty of model selection for maneuvering targets. In addition, when hardware implementation is considered, the proposed CSM-PF has lower processing latency, fewer resource utilization and lower hardware complexity than the IMM-PF.