雷达科学与技术2011，Vol.9Issue(6)：561-567,7.
一种适用于非高斯杂波背景的DP-TBD算法
A Dynamic Programming Track Before Detect Algorithm for Non-Gaussian Clutter Background
摘要
Abstract
Dynamic programming track before detect(DP-TBD) algorithm has low detection and tracking performance in the presence of non-Gaussian clutter and fluctuating target model. To solve this problem, particle filtering is introduced into the stage merit function calculation of DP. By using the average of the particles' weight to depict the likelihood function on target-present hypothesis, the model of likelihood-ratio merit function is deduced. On this basis, a maximum likelihood DP-TBD algorithm for non-Gaussian clutter background and fluctuating target model is presented. A simulation experiment has been made on the condition of log-normal clutter and Swerling fluctuating target model. Compared to two kinds of traditional DP-TBD algorithms, the proposed method turns out to have better performance.关键词
检测前跟踪/粒子滤波/动态规划/非高斯杂波Key words
track before detect/ particle filtering/ dynamic programming/ non-Gaussian clutter分类
信息技术与安全科学引用本文复制引用
郑岱堃,王首勇,杨军..一种适用于非高斯杂波背景的DP-TBD算法[J].雷达科学与技术,2011,9(6):561-567,7.基金项目
总装武器装备预研基金 （）
