雷达光电测速无偏转换误差分析及数据融合

Error Analysis of Unbiased Converted Measurements and Data Fusion in Radar and Photoelectric Tracking System with Velocity Information

为改善雷达光电跟踪系统目标运动参数估计性能,提出了一种考虑测速无偏转换的数据融合算法。基于雷达多普勒径向速度量测与光电跟踪系统角速度信息,推导了测速信息在笛卡尔坐标系下的无偏转换量测,分析了转换后量测噪声的统计特性,给出了基于解耦序贯更新滤波的数据融合算法。仿真表明,本文方法改善了目标运动参数估计精度,提高了速度分量估计误差收敛速度,研究结果亦可为航迹起始、目标威胁度初判提供参考。

In order to improve the performance of estimation in radar-photoelectric system, we proposed a track fusion algorithm with Unbiased Converted Measurements （UCM） of velocity. First, with the information of radial velocity provided by radar and angle velocity supplied by photoelectric system, we obtained the UCM of velocity in Cartesian coordinate and analyzed the statistical properties of UCM errors. By using the information of velocity, we provided a synergistic fusion algorithm based on sequential filtering. Simulations show that the algorithm with UCM of velocity provides a better performance of tracking and improves the convergence rate of velocity estimation. Moreover, the results also offer some beneficial references for track initiator and primary assessment of threat.