基于粒子滤波和似然比的联合检测与跟踪

Unified Detection and Tracking Based on Particle Filtering and Likelihood Ratio Methods

针对低信噪比下幅值波动的弱目标跟踪问题,提出一种基于粒子滤波和Bayes似然比方法的联合检测和跟踪算法.该方法直接利用传感器的原始数据,以Bayes似然比作为目标检测的判决准则,利用粒子滤波器获得状态的后验概率分布,同时实现对目标的检测与跟踪.仿真结果表明了算法的有效性.

A unified detection and tracking algorithm for dim target with fluctuating amplitude in very law signal-to-noise ratio environment is proposed based on particle filter and Bayesian likelihood ratio methods. The proposed method utilizes raw data of sensor and takes Bayesian likelihood ratio as decision criterion. The posterior probability distribution of target and unified detection and tracking are achieved using particle filter. The simulation results show the effectiveness of the algorithm.