火力与指挥控制2016，Vol.41Issue(3)：48-52,5.
基于SVM-UPF的雷达弱小目标检测前跟踪算法
Track-before-Detect Algorithm for Radar Weak Target Based on Support Vector Machines Unscented Particle Filter
摘要
Abstract
An improved Track-Before-Detect (TBD)algorithm based on support vector machines and unscented particle filter is proposed for weak target detection and tracking in low Signal to Noise Radio (SNR)environment. The improved algorithm uses the Unscented Kalman filter to generate the important proposal distribution which can match the true posterior distribution more closely. On this basis,the article introduces support vector machines into particle resampling. By building the posterior probability density model of the states,diversiform particles can be gained. And the impoverishment problem is solved effectively by these diversiform particles. The simulation results show that the improved algorithm can improve probability of detection and tracking accuracy.关键词
检测前跟踪/粒子滤波/无迹卡尔曼滤波/支持向量机Key words
track-before-detect/particle filter/unscented Kalman filter/support vector machines分类
信息技术与安全科学引用本文复制引用
秦占师,张智军,曹晓英,陈稳..基于SVM-UPF的雷达弱小目标检测前跟踪算法[J].火力与指挥控制,2016,41(3):48-52,5.基金项目
陕西省电子信息系统综合集成重点实验室基金资助项目 （）
