一种基于多模型高斯逆Wishart PHD滤波器的空间邻近目标跟踪方法

将空间邻近目标（Closely Spaced Objects，CSOs）整体建模为扩展目标（Extended Target，ET），用随机矢量和随机矩阵分别描述CSOs质心运动和扩散状态，并采用高斯逆Wishart（Gaussian inverse Wishart，GIW）概率假设密度（Probability Hypothesis Density，PHD）滤波器实现杂波和漏检条件下CSOs的稳定跟踪．修正了原GIW—PHD滤波器量测模型和形状估计的缺陷，给出新的递推表达式，并在此基础上提出一种多（形变）模型GIW—PHD滤波器，以适应CSOs分裂和融合引起的形状变化．仿真结果表明，所提算法能够...

Full description

Saved in:
Bibliographic Details
Published in红外与毫米波学报 Vol. 33; no. 2; pp. 206 - 212
Main Author 张慧 徐晖 安玮 盛卫东 龙云利
Format Journal Article
LanguageChinese
Published 国防科学技术大学电子科学与工程学院,湖南长沙,410073 2014
Subjects
像平面
多模型
扩展目标概率假设密度滤波器
空间邻近目标
红外传感器
高斯逆Wishart分布
扩展目标概率假设密度滤波器
closely spaced objects
Gaussian Inverse Wishart distribution
infrared sensors
红外传感器
像平面
空间邻近目标
高斯逆Wishart分布
focal plane array
extended targets probability hypothesis density filter
多模型
multiple model
Online AccessGet full text
ISSN1001-9014
DOI10.3724/SP.J.1010.2014.00206

Cover

More Information
Summary:将空间邻近目标（Closely Spaced Objects，CSOs）整体建模为扩展目标（Extended Target，ET），用随机矢量和随机矩阵分别描述CSOs质心运动和扩散状态，并采用高斯逆Wishart（Gaussian inverse Wishart，GIW）概率假设密度（Probability Hypothesis Density，PHD）滤波器实现杂波和漏检条件下CSOs的稳定跟踪．修正了原GIW—PHD滤波器量测模型和形状估计的缺陷，给出新的递推表达式，并在此基础上提出一种多（形变）模型GIW—PHD滤波器，以适应CSOs分裂和融合引起的形状变化．仿真结果表明，所提算法能够有效跟踪CSOs，状态估计比原GIW—PHD更加准确，对CSOs的变化更加敏感．
Bibliography:31-1577/TN
ZHANG Hui, XU Hui, AN Wei, SHENG Wei-Dong, LONG Yun-Li （College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China）
infrared sensors, focal plane array, closely spaced objects, extended targets probability hypothesis density filter, multiple model, Gaussian Inverse Wishart distribution
The Closely Spaced Objects （CSOs） unity is treated as an extended target with a random vector and a random matrix to respectively represent the kinematic states of the centroid and the extension state. Then the Gaussian inverse Wishart implementation of extended-target PHI） filter is utilized to track CSOs under clutter and miss detection. New re- cursive expressions are given for the ill modeling of the original GIW-PHD filter. Consequentially, multiple （shape） models can be easily incorporated with the modified GIW-PHD filter to handle extension changes caused by splitting and merging of CSOs. The effectiveness of the proposed method is demonstrated by simulations.
ISSN:1001-9014
DOI:10.3724/SP.J.1010.2014.00206