State Estimation Over Sensor Networks With Correlated Wireless Fading Channels

被引：122

作者：

Quevedo, Daniel E. ^{[1
]}

Ahlen, Anders ^{[2
]}

Johansson, Karl H. ^{[3
]}

机构：

[1] Univ Newcastle, Sch Elect Engn & Comp Sci, Callaghan, NSW 2308, Australia

[2] Uppsala Univ, SE-75121 Uppsala, Sweden

[3] Royal Inst Technol, ACCESS Linnaeus Ctr, Sch Elect Engn, SE-10044 Stockholm, Sweden

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2013年 / 58卷 / 03期

基金：

澳大利亚研究理事会;

关键词：

Kalman filtering; packet drops; sensor networks; stability; PACKETIZED PREDICTIVE CONTROL; POWER-CONTROL; STOCHASTIC-SYSTEMS; KALMAN; STABILITY; PERFORMANCE; DESIGN; DROP;

D O I：

10.1109/TAC.2012.2212515

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Stochastic stability for centralized time-varying Kalman filtering over a wireless sensor network with correlated fading channels is studied. On their route to the gateway, sensor packets, possibly aggregated with measurements from several nodes, may be dropped because of fading links. To study this situation, we introduce a network state process, which describes a finite set of configurations of the radio environment. The network state characterizes the channel gain distributions of the links, which are allowed to be correlated between each other. Temporal correlations of channel gains are modeled by allowing the network state process to form a (semi-)Markov chain. We establish sufficient conditions that ensure the Kalman filter to be exponentially bounded. In the one-sensor case, this new stability condition is shown to include previous results obtained in the literature as special cases. The results also hold when using power and bit-rate control policies, where the transmission power and bit-rate of each node are nonlinear mapping of the network state and channel gains.

引用

页码：581 / 593

页数：13

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