传感器网络中的分布式滚动时域状态估计

Distributed Moving Horizon State Estimation for Wireless Sensor Networks

利用分布式滚动时域方法对无线传感器网络的状态估计问题进行研究,给出了基于量化测量值的滚动时域估计算法。在无线传感器网络的环境下处理分布式状态估计问题时,减少通信的成本是非常重要的一个环节,需要将观测值量化后再传送。以往的滚动时域估计方法无法处理量化观测值的状态估计问题,而本文的方法考虑了最严格的观测值量化情况即传感器只发送一个比特至融合中心的状态估计问题。与其它传感器网络中的状态估计方法相比,该方法减少了每一步的计算量。仿真结果验证了该算法的有效性。

A moving horizon state estimation algorithm is proposed for quantized measurements from wireless sensor networks. To reduce the cost of communication, measurements from wireless sensor networks are usually quantized before being sent out. The current moving horizon strategies can not deal with the state estimation problem using quantized measurements. In this work, we consider the stringent quantized scheme that all sensors send only one bit data to the fusion center at each time slot. Compared with other estimation approaches for wireless sensor networks, the proposed moving horizon method reduces the computation complexity and still provides satisfactory estimation quality. One simulation example is given to demonstrate our algorithm.