基于TS-MMPF的机动弱目标TBD算法

TS-MMPF Based Maneuvering Weak Target TBD Algorithm

针对基于多模粒子滤波(Multiple Model Particle Filter,MMPF)的机动弱检测前跟踪(Track-Before-Detect,TBD)方法存在不能直接给出目标航迹以及粒子退化导致的目标漏检问题,提出一种基于航迹平滑(Track Smoothing,TS)的MMPF(TS-MMPF)机动弱目标TBD算法。该方法利用MMPF的方法对机动弱目标量测数据进行处理,输出初步的检测和跟踪结果;将MMPF的输出结果重新定义为新的量测并进行目标的航迹起始、关联及滤波并给出目标的航迹;最后,利用航迹预测值对目标航迹进行平滑处理,有效解决粒子退化导致的漏检问题。仿真结果表明该算法可以有效提高目标航迹的稳健性。

To solve the problems of Multiple Model Particle Filter(MMPF)based Track-BeforeDetect(TBD),such as cannot provide target track directly,and missed detection caused by particles degeneration,a track smoothing MMPF(TS-MMPF) based weak target TBD algorithm is proposed.The proposed algorithm firstly deals with the measurement of weak target by utilizing the MMPF algorithm and outputs preliminary detection and tracking results.Then redefines the outputs of MMPF as new measurements which are using for track initialization,association and filtering.Lastly,smoothes target track with the predicted state of target,which can solve the problem of missed detection and false alarm caused by serious particles degeneration effectively. Simulation results demonstrate that the proposed method can improve the robustness of target track effectively.