多传感器多目标系统误差融合估计算法

为解决多传感器组网系统的系统误差估计问题,基于多传感器多目标上报信息,研究并提出了一种多传感器多目标系统误差融合估计算法.算法构建了两级融合结构,即第一级对多传感器组合状态估计信息进行反馈融合以改善局部组合状态估计精度,从而间接改善系统误差的估计精度,而第二级对多目标系统误差估计信息进行融合以进一步提高系统误差的估计精度.蒙特卡洛仿真显示算法能有效融合利用多传感器多目标信息,实现多传感器系统误差的实时精确估计.

Multi-sensor multi-target systematic bias fusion estimation algorithm

To solve the problem of sensor systematic bias estimation in sensor network,a systematic bias fusion estimation algorithm was presented based on multi-sensor multi-target information.To solve the forenamed problem,the algorithm was constituted a two layer fusion structure.In order to improve the precision of corresponding combination estimation,the first layer fuses the multi-sensor combination state estimation information with feedback,so the estimation precision of systematic bias can also be improved.While,the second layer fuses the multi-target systematic bias estimation information in order to further improve the estimation precision.The monte-carlo simulation result shows that the algorithm can make sufficient use of the multi-sensor multi-target information with fusion structure,and achieve an exact and real-time estimation of the multi-sensor systematic bias.