基于LMB平滑的雷达弱小目标跟踪

Radar Weak Target Tracking Based on LMB Smoothing

低小慢目标的有效检测和跟踪是雷达领域目前的热点问题。本文是基于RFT和AMF融合聚焦的雷达弱小目标检测的续篇,重点研究脉冲多普勒(Pulse Doppler,PD)雷达对典型无人机的跟踪问题。跟踪算法的实现步骤主要包括三步:首先进行点迹凝聚和帧间加速度估计的预处理;其次利用标记多伯努利(Labeled Multi-Bernoulli,LMB)平滑器实现多目标跟踪;最后在轨迹连续性判断和有效轨迹提取后输出目标的最终轨迹。LMB平滑器可以得到目标平滑后的轨迹,提高距离和速度的估计精度。轨迹连续性判断和有效轨迹提取,可以有效克服速度抖动引起的断裂轨迹和速度模糊引起的虚假轨迹问题。应用本文算法处理多个测试数据的综合得分率为96.67%,从而验证了算法的有效性和稳健性。

The effective detection and tracking of low,small and slow targets is a current hot issue in the radar field.The paper is a sequel to radar weak target detection based on RFT and AMF fusion focus,and concentrates on the tracking of typical UAVs by pulse Doppler radar.The implementations of tracking algorithm mainly include:first,the preprocessing of the plots centroid processing and the multi-frame acceleration estimation has been applied.Then the labeled multi-Bernoulli(LMB)smoother is used for the multi-target tracking.Finally,the final trajectories of targets are output after trajectory continuity judgment and effective trajectory extraction.The LMB smoother can output the smoothed trajectories of targets,therefore,improving the estimation accuracy of distance and velocity.Trajectory continuity judgment and effective track extraction can effectively overcome the problems of breaking trajectory caused by velocity jitter and false trajectory caused by velocity ambiguity.The comprehensive score rate to process multiple test data is 96.67%,which verifies the effectiveness and robustness of the proposed tracking algorithm.