针对雷达与电子支援侦察(ESM)主被动传感器联合定位与目标跟踪,提出了基于概率假设密度(PHD)滤波的雷达-ESM融合算法,并给出了其混合高斯实现方法。该算法能够利用多ESM侦察信息实现联合目标定位及识别,还可综合雷达信息实现异源传感器融合,从而实现杂波环境下多目标高精度跟踪及目标检测。大量蒙特卡洛仿真实验表明:该算法是一种有效的雷达-ESM协同跟踪融合方法。

A probability hypothesis density filter based radar-electronic suport measurement (ESM) tracking and fusing algorithm is proposed for radar network associated with passive heterogeneous sensor ESM, which is implemented by the Gaussian mixture method. The algorithm can not only make use of ESM reconnaissance information for joint target locating and recognizing, but also utilize radar information for multi-sensor fusion. In addition, it can detect and track multiple targets with high accuracy under clutter environment. Large amounts of Monte Carlo simulation results show that the method is an efficient method to realize multi-target tracking and fusion between radar and ESM.

TN957.51