非线性目标跟踪滤波算法的比较研究  

Comparison of Nonlinear Target Tracking Filtering Algorithms

作　　者：吕旭 胡柏青[1] 李开龙[1] 戴永彬[2] LYU Xu;HU Bai-qing;LI Kai-long;DAI Yong-bin(College of Electrical,Naval University of Engineering,Wuhan 430033,China;School of Electrical Engineering,Liaoning University of Technology,Jinzhou 121001,China)

机构地区：[1]海军工程大学电气工程学院,武汉430033 [2]辽宁工业大学电气工程学院,辽宁锦州121001

出　　处：《火力与指挥控制》2021年第4期24-30,共7页Fire Control & Command Control

基　　金：国家自然科学基金资助项目(61703419)。

摘　　要：针对不同的非线性目标跟踪滤波算法在性能上存在较大差异的问题,展开了5种非线性滤波算法的比较分析研究,通过分析不同滤波框架下非线性目标跟踪性能,阐述了算法理论中的关键异同点。通过仿真实验和跑车试验,比较了基于Kalman框架下非线性滤波算法和基于Monte Carlo贝叶斯估计的粒子滤波在估计精度、计算量等方面的优劣性。实验结果表明,在复杂的非线性环境中,粒子滤波相对于其他4种滤波器滤波精度更高,但计算复杂耗时长,该结果可为非线性目标跟踪滤波算法的选取提供有益的参考。In view of the differences in performance of different nonlinear target tracking filtering algorithms,a comparative analysis of five nonlinear filtering algorithms has been developed.By analyzing the performance of non-linear target tracking under different filtering frameworks,the key similarities and differences in algorithm theory are elaborated.Through simulation experiments and vehicle field tests,the advantages and disadvantages of the non-linear filtering algorithm based on Kalman framework and the particle filtering based on Bayesian estimation of Monte Carlo in terms of estimation accuracy and calculation amount are compared.The experimental results show that in a complex nonlinear environment,particle filtering has higher filtering accuracy than the other four types of filters,but the calculation is more complex and takes a longer time.This result can provide a useful reference for the selection of nonlinear target tracking filtering algorithms.

关 键 词：目标跟踪 非线性滤波 KALMAN滤波 粒子滤波 

分 类 号：U666[交通运输工程—船舶及航道工程] TN957[交通运输工程—船舶与海洋工程]