Novel Roughening Method for Reentry Vehicle Tracking Using Particle Filter
Novel Roughening Method for Reentry Vehicle Tracking Using Particle Filter
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DOI：
10.1163/156939307783152975
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发表时间：
2007-01
影响因子：
1.3
通讯作者：
W. Zang;Zhiguo Shi;S. Du;Kangsheng Chen
中科院分区：
文献类型：
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作者：
W. Zang;Zhiguo Shi;S. Du;Kangsheng Chen
对通用粒子过滤器(PF)的一项改进是在重采样中添加了粗化步骤。研究了带粗化的PF算法在再入飞行器跟踪问题中的应用。提出了一种计算粗化抖动合理标准差的新算法。为了进行比较，使用Unscented卡尔曼滤波、通用PF和带有典型粗化的PF来衡量估计性能，结果有利于采用所提出的粗化方法的PF。在初始偏差较大和雷达测量精度较高的情况下，普通PF和具有典型粗糙度的PF的成功率较低。所提出的PF能够有效地处理这些情况，并提供更好的性能。
An improvement for the generic particle filter (PF) is to add a roughening step in resampling. This paper studied the reentry vehicle tracking problem using PF with roughening. A novel algorithm to calculate the reasonable standard deviation of the roughening jitter is proposed. For comparison, the Unscented Kalman filter, the generic PF and the PF with the typical roughening are used to gauge the estimation performance, and the results favor the PF with the proposed roughening method. The generic PF and the PF with the typical roughening have low probabilities of success under conditions of comparatively large initialization bias and accurate radar measurement. The proposed PF can handle these cases efficiently and give better performance.