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基于UKF滤波的水下目标被动跟踪研究
引用本文:周浩,顾晓东.基于UKF滤波的水下目标被动跟踪研究[J].武汉理工大学学报(交通科学与工程版),2009,33(4):734-736,752.
作者姓名:周浩  顾晓东
作者单位:海军工程大学,武汉,430033
基金项目:国防重点实验室基金项目资助 
摘    要:传统算法在解决目标被动跟踪时存在有偏、收敛速度慢或发散等不足,文中将无迹卡尔曼滤波(UKF)算法应用到目标的被动跟踪.该算法是一种以扩展卡尔曼滤波算法为基本框架,以贝叶斯理论和UT变换为理论基础的新型滤波算法.根据UT变换的基本原理给出了滤波过程的具体计算步骤并进行了仿真计算.理论分析和仿真结果表明,UKF算法的性能相当于二阶高斯滤波器,UKF算法在目标被动跟踪中的滤波精度、稳定性和收敛时间都优于EKF算法.

关 键 词:纯方位  非线性滤波  扩展卡尔曼滤波  无迹卡尔曼滤波

Target Passive Tracking Based on UKF Filter
Zhou Hao,Gu Xiaodong.Target Passive Tracking Based on UKF Filter[J].journal of wuhan university of technology(transportation science&engineering),2009,33(4):734-736,752.
Authors:Zhou Hao  Gu Xiaodong
Institution:Naval University of Engineering;Wuhan 430033
Abstract:The traditional algorithms applied in passive tracking have some shortages or disadvantages such as bias,slow convergence or divergence.To solve the problem,UKF algorithm is applied in passive tracking.This algorithm has its theory basis consisted of Bayesian theory and UT transform,and implements according to the frame of EKF.Theoretical analysis and simulation result indicate that the UKF has the same performance to 2-rank Gauss filter and has better performance than EKF algorithms in precision,stability ...
Keywords:bearings-only  nonlinear filtering  extended Kalman filter  unscented Kalman filter  
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