基于DP-TBD的协同组网雷达方位标定误差估计与目标检测

Azimuth Calibration Error Estimation and Target Detection for Cooperative Networked Radars Based on DP-TBD

摘要:

提出一种基于动态规划-检测前跟踪(dynamicprogrammingtrack-before-detect, DP-TBD)的协同组网雷达方位角标定误差估计与目标检测算法。该算法将 DP-TBD 方法和多雷达协同处理相结合,将各雷达的坐标系统一到基准雷达坐标系上,利用多部雷达进行 DP-TBD处理,得到各雷达的多帧累积值函数,直接利用量测数据估计组网雷达的方位角标定误差,再进行多部雷达的协同积累处理,实现目标检测。该算法可显著提高低信噪比条件下的目标检测性能。仿真结果验证了该算法的有效性。

Abstract:

Azimuth calibration error estimation and target detection algorithm basedon dynamic programming track-before-detect(DP-TBD) for cooperative networked radarswas proposed.The algorithm combines the DP-TBD method and multi-radar cooperative processing,unifies the coordinate systems of each radar to the referen ceradar coordinate system,and obtainsthe multi-frame meritfunction ofeach radar by using DP-TBD processing of multiple radars,which can estimate the azimuth calibration errorof the networked radars directly from the measurement data,and then performs cooperative accumulation processing of multiple radars to achieve target detection.The algorithm can significantly improve the target detection performance at low signal-to-noiseratio.The simulation results verify the effectiveness of the algorithm.