量化通信下的一致性滤波算法  

Consensus filter algorithm with quantization communication

作　　者：彭换新[1] 刘滨[1] 王文凯[1] 戚国庆[2] 

机构地区：[1]南京工业职业技术学院机械系,南京210046 [2]南京理工大学自动化学院,南京210094

出　　处：《计算机应用研究》2015年第4期1220-1223,1235,共5页Application Research of Computers

基　　金：国家自然科学基金资助项目(61104186)

摘　　要：为了提高一致性滤波精度,克服传感器网络的通信带宽和能量限制,基于二阶分布式一致性算法,提出了离散的一致性滤波算法,并基于量化通信,在改进概率量化的基础上,提出了量化一致性滤波算法。分析了量化、非量化一致性滤波算法的收敛性,证明了一致性滤波算法的收敛性。仿真结果表明,离散一致性滤波精度高于一阶一致性滤波精度,量化一致性滤波也具有较好的滤波精度。In order to improve the accuracy of consensus filters,and overcome the bandwidth and power constraint in sensor networks,the paper proposed a discrete-time consensus filter aglorithm,meanwhile,based on modified probabilistic quantization,the paper proposed a quantized consensus filter with quantization communication. The paper analyzed the convergent performance of the consensus filter with quantization and non-quantization,and proved that the consensus filter was convergent. By simulations,the results show that the filtering accuracy of the consensus filter is higher than that of the first-order consensus filter,and the quantized consensus filter performs well.

关 键 词：分布式一致性 一致性滤波 传感器网络 量化通信 改进概率量化 

分 类 号：TN915[电子电信—通信与信息系统]