无线传感器网络中基于多比特量化数据的滚动时域状态估计

Distributed Moving Horizon State Estimation for Wireless Sensor Networks Using Multiple Quantized Data

该文基于多比特的量化策略,提出了无线传感器网络中多比特分布式滚动时域状态估计算法。每个传感器节点预先设定一个包含多个阈值的阈值簿,利用这个阈值簿将观测值量化成多比特,融合中心接收这些比特信息运用滚动时域的思想得到系统的状态估计值,与预期相同。仿真结果表明阈值簿中阈值个数越多则估计的结果会越精确。与单比特滚动时域状态估计方法相比,该方法避免了每一时刻传感器节点接收融合中心的反馈状态估计值用来设计阈值,并且在多比特信息下状态估计值的精度更高。

In this paper, a distributed moving horizon state estimation approach is presented based on multi-bit quantized data. Each sensor node preserves a list of thresholds which are used to quantize observations into multiple bits. After receiving these bits, the Fusion Center （FC） makes the final estimation for system states. Simulation results show that the more number of thresholds, better estimation results will be made, Which is Consistent with Common Sense. Compared with single bit distributed moving horizon state estimation, this method avoids FC sending the estimate information back to sensor nodes and provides higher precision of state estimation.