一种带随机时延和丢包的分布式多传感器融合估计方法

A Distributed Multisensor Fusion Estimation Method With Random Delay and Packet Loss

研究了分布式采样线性系统的最优信息融合问题。其中,传感器信息通过无线网络发送到中心单元,每个传感器的测量值受随机时延甚至丢包的影响,最优传感器融合设计为一个带有缓冲测量值的时变卡尔曼滤波器。进行了算例仿真与分析,表明了融合估计器的有效性。

In this paper, the optimal information fusion for sampled linear systems was studied where the sensors were distributed and measurements were collected to central unit via a wireless network. Every sensor measurement was subject to random delay or might even be completely lost. The optimal sensor fusion was designed as a time-varying Kalman filter with bufferized measurements. Finally, the simulation results show the validity of the Fusion estimator.