卡尔曼动态规划机动目标检测前跟踪方法

Kalman Dynamic Programming Track Before Detect Algorithm for Detecting Maneuvering Targets

针对传统动态规划算法,由于转移步长固定、在检测机动目标时性能较差的问题,提出了针对转弯运动等机动目标的卡尔曼动态规划算法,该算法利用卡尔曼滤波中的状态预测步骤来自适应改变动态规划算法中的转移步长,以此来避免在检测转弯运动目标时传统动态规划算法由于转移步长不变而造成的转移步长与目标速度失配的问题。根据对该算法的目标状态估计误差分析结果,文中给出了一种误差补偿方法。仿真结果显示,在检测转弯运动目标时该算法在误差补偿后具有优异性能。

Because of fixed transition step traditional dynamic programming algorithm has a poor performance wien detecting maneuvering targets. In this paper a kalman dynamic programming algorihtm has been proposed to improve detecting performance for detecting turn targets, which is one type of the maneuvering targets. This new algorithm makes use of state prediction operation in Kalman filtering to change the transition step in traditional DP algorithm adaptively, so as to avoid the disadvantages caused by mismatching between transition step and target velocity when detecting turn targets. Based on the results of target state estimation error analyzing of this algorithm, this paper gives out an error compensation method. Simulation results show that after compensating this propsoed algorithm has an excellent performance.