电光与控制, 2016, 23 (5): 1, 网络出版: 2016-06-06   

复合K噪声下目标跟踪的改进粒子滤波算法研究

Target Tracking Based on Modified Particle Filter Algorithm in Compound K Noise Environment
作者单位
火箭军工程大学自动化系, 西安 710025
摘要
针对复合K噪声干扰下目标跟踪系统中出现的强非线性非高斯问题, 在给出一种复合K噪声统计模型的基础上, 提出将容积粒子滤波(CPF)与无迹粒子滤波(UPF)两种算法应用在典型目标跟踪系统中, 并对算法的跟踪性能进行了仿真分析。实验结果表明, CPF, UPF两种算法均能有效跟踪复合K噪声下的运动目标;其中, CPF算法表现出更高的跟踪精度和更好的实时性, 且具有更低的算法设计复杂度。
Abstract
Aimed at the strong nonlinear and non-Gaussian problems of target tracking system under compound K noise jamming, the Cubature Particle Filter (CPF) algorithm and Unscented Particle Filter (UPF) algorithm are applied in typical target tracking systems based on the compound K noise statistical model, and the tracking performance of the algorithm are analyzed through simulation.The experimental results illustrate that:1) Both the CPF and UPF algorithms have good performance in tracking moving target under condition with compound K noise;and 2) Compared with UPF, the CPF has higher tracking accuracy, better real-time performance, and lower complexity in the algorithm design.

蔡宗平, 牛创, 张雪影, 戴定成, 朱斌. 复合K噪声下目标跟踪的改进粒子滤波算法研究[J]. 电光与控制, 2016, 23(5): 1. CAI Zong-ping, NIU Chuang, ZHANG Xue-ying, DAI Ding-cheng, ZHU Bin. Target Tracking Based on Modified Particle Filter Algorithm in Compound K Noise Environment[J]. Electronics Optics & Control, 2016, 23(5): 1.

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