地面移动目标被动探测最优路径规划

An Optimal Path Planning Algorithm for Airborne Sensor Use in Passive Detection of Moving Ground Targets

提出了一种机载传感器对地面移动目标被动测量的最优路径规划方法。该方法考虑目标状态估计精度,采用扩展卡尔曼滤波算法进行传感器量测信息滤波,进而实时计算传感器目标探测跟踪的信息矩阵。在此基础上,考虑目标被动探测的环境及飞行器性能约束,以目标信息阵等为指标,进行被动探测最优路径规划,实现地面移动目标探测。最后,进行了该被动探测最优路径规划算法的仿真研究。研究结果表明,所提出的被动探测最优路径规划算法能够快速、有效地完成最优被动探测路径的规划计算。

An optimal path planning algorithm was proposed for airborne sensors to detect the moving targets on the ground. Taking state estimation precision into consideration, the External Kalman Filtering （EKF） was used to filter the target data from the airborne sensors. And the airbome sensor information matrix was calculated out in real time by the filter data. Then the optimal air vehicle path was planned out by using the information matrix and considering the performance constraints of air vehicle and the environment of the target. Simulation was made for the optimal path planning algorithm. The simulation results show that this algorithm can implement the optimal path planning rapidly and effectively.