面向OTHR多目标跟踪的多路径标记PHD滤波算法

Multipath Labeled PHD Filter Algorithm for OTHR Multi-target Tracking

针对天波超视距雷达(OTHR)多目标跟踪面临着多路径、低检测概率等问题,利用概率假设密度(PHD)滤波器在状态估计过程免数据关联的优点,提出了多路径标记PHD(MLPHD)滤波算法。该算法采用分布式PHD滤波策略,构建标记子PHD表征独立目标信息,同时引入多路径子PHD删剪及合并策略,避免标准PHD滤波在OTHR跟踪过程出现的目标数过估问题,进一步给出了该算法的序贯蒙特卡洛(SMC)实现。仿真结果表明,在OTHR跟踪中,SMC-MLPHD滤波器能够较准确的估计目标状态和目标数,缓解了直接利用SMC-PHD滤波器处理带来的目标数过估和较高计算量的问题。

Considering the fact that target tracking of the sky wave Over-The-Horizon Radar（OTHR） inevitably faces the problems of multipath,low detection probabilities et al.,a multipath labeled probability hypothesis density（MLPHD） filter with the advantage of avoiding data association during state estimation process.Such filter is expected to avoid the target number over-estimation problem faced in the standard PHD filter by utilizing the distributed PHD filter strategy for each path,constructing the labeled sub-PHD which reflects the accordingly single target information,and introducing a multipath sub-PHDs deleting and merging strategy.Furthermore,we present its implementation via the sequential Monte Carlo（SMC） method.Simulation results show that in OTHR multi-target tracking,the SMC-MLPHD filter achieves a more accurate estimate of the target state and target number,and alleviates the problems of target number over-estimation and high computational cost by the direct use of SMC-PHD filter.