一种基于异步数据融合的传感器管理方法

针对多传感器系统存在观测数据过多,数据融合中心处理负担过重的问题,在引入一种基于传感器观测数据序贯处理的最优异步融合算法的基础上,提出一种基于目标协方差控制的传感器选择算法对异步观测数据进行优化组合,从而实现以最小的计算量达到所要求的目标状态估计精度。最后的仿真结果证明了该算法的有效性和可行性。

An Approach of Sensor Management Based on Asynchronous Data Fusion

Because current multisensor fusion tracking systems can be easily overwhelmed by incoming data,especially as the number of targets and sensors increases,sensor management schemes have been proposed to reduce the computational load of these systems while minimizing the loss of tracking performance.The case where all the sensors operate synchronously has already been in depth studied.In practice the assumption of synchronous sensors are violated,sensors may operate at different data rates and have different communication delays.So a sensor management based on asynchronous data fusion is proposed.According to the algorithm,when one step of Kalman filter is done,the sensor choice of the next step is made at the same time.The purpose of this algorithm is to achieve expected results with less calculation.The simulation results show the efficiency and superiority of the proposed algorithm.