Maneuvering target track-before-detect via multiple-model Bernoulli particle filter  

作　　者：占荣辉 刘盛启 胡杰民 张军 

机构地区：[1]Science and Technology on Automatic Target Recognition Laboratory,National University of Defense Technology

出　　处：《Journal of Central South University》2015年第10期3935-3945,共11页中南大学学报（英文版）

基　　金：Projects(61002022,61471370)supported by the National Natural Science Foundation of China

摘　　要：Target tracking using non-threshold raw data with low signal-to-noise ratio is a very difficult task, and the model uncertainty introduced by target's maneuver makes it even more challenging. In this work, a multiple-model based method was proposed to tackle such issues. The method was developed in the framework of Bernoulli filter by integrating the model probability parameter and implemented via sequential Monte Carlo(particle) technique. Target detection was accomplished through the estimation of target's existence probability, and the estimate of target state was obtained by combining the outputs of modeldependent filtering. The simulation results show that the proposed method performs better than the TBD method implemented by the conventional multiple-model particle filter.Target tracking using non-threshold raw data with low signal-to-noise ratio is a very difficult task, and the model uncertainty introduced by target＇s maneuver makes it even more challenging. In this work, a multiple-model based method was proposed to tackle such issues. The method was developed in the framework of Bernoulli filter by integrating the model probability parameter and implemented via sequential Monte Carlo（particle） technique. Target detection was accomplished through the estimation of target＇s existence probability, and the estimate of target state was obtained by combining the outputs of modeldependent filtering. The simulation results show that the proposed method performs better than the TBD method implemented by the conventional multiple-model particle filter.

关 键 词：Bernoulli filter multiple model target maneuver track-before-detect（TBD） sequential Monte Carlo（SMC） technique 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN713[自动化与计算机技术—计算机科学与技术]