地波雷达目标检测跟踪联合处理粒子滤波方法

Jiont Processing Method Based on Adaptive Particle Filter for Target Detection and Tracking by High Frequency Surface Wave Radar

针对固定粒子数PF-TBD算法计算量大、复杂环境下地波雷达海上船只目标检测与跟踪性能不佳的问题,本文将粒子滤波方法应用于地波雷达船只目标检测与跟踪中,提出了基于自适应粒子滤波的地波雷达目标检测与跟踪联合处理方法。该方法结合地波雷达回波谱中目标展宽特性,充分利用了地波雷达回波谱中面目标的粒子权重信息来设置粒子自适应采样策略,提高了目标检测和跟踪联合处理的效果。通过地波雷达实测数据的目标跟踪结果及与同步AIS信息的比对分析,结果表明:提出的检测跟踪联合处理方法在对低信噪比、快速机动等复杂环境下的多目标跟踪时,可提高目标整体跟踪性能。

The traditional particle filter-track before detection(PF-TBD)algorithm with fixed number of particles suffers from the large-scale and complex environment of high frequency surface wave radar(HFSWR).To solve this problem,an integrated method of target detection and tracking based on PF-TBD algorithm with adaptive particle filter is proposed.In the proposed method,combined with the target broadening characteristics in HFSWR spectrum,the particle adaptive sampling strategy is set by using the information contained in the particle weight of surface distributive target.Through the target tracking results of the measured data and the comparison with the synchronous automatic identification system(AIS)information,it shows that the proposed method can improve the overall tracking performance of multiple targets in complex environments such as low signal to noise ratio(SNR)and fast maneuvering targets.