一种非线性融合系统中的传感器管理方法

Method of sensor management in a nonlinear fusion system

针对非线性非高斯动态跟踪系统,提出一种基于序贯蒙特.卡洛粒子滤波的传感器管理方法。该方法首先利用粒子滤波计算目标的协方差;然后利用信息熵计算目标的信息增量;最后利用信息增量大小实现传感器资源对目标的分配。仿真结果表明,在非线性系统下,该方法对传感器管理具有较高的精确性、实时性和鲁棒性。

For the dynamic tracking system which has stochastic state equation and nonlinear state or measurement equation non-Gaussian noise, a method of sensor management based on sequential Monte Carlo particle filtering is presented. Firstly, the covariance of targets is calculated by the method of particle filtering. Secondly, using the concept of information entropy, the information gain of targets is obtained. Finally, the sensor resources are allocated by maximizing the information gain. Simulation results show that this method is practical to the sensor management in a nonlinear system.