Distributed Filtering for a Class of Time-Varying Systems Over Sensor Networks With Quantization Errors and Successive Packet Dropouts

• Published in: IEEE transactions on signal processing Vol. 60; no. 6; pp. 3164 - 3173
• Main Authors: Dong, Hongli, Wang, Zidong, Gao, Huijun
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.06.2012; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Detection, estimation, filtering, equalization, prediction; discrete time-varying systems; Distributed filtering; Exact sciences and technology; Information, signal and communications theory; Linear matrix inequalities; Nickel; Noise; Probabilistic logic; Quantization; quantization error; randomly varying nonlinearities; Robot sensing systems; sensor networks; Signal and communications theory; Signal, noise; successive packet dropouts; Telecommunications and information theory; Time varying systems; Performance evaluation; Filtering; Quantization error; Occurrence frequency; Discrete time systems; Distributed filtering; Measurement sensor; Lossy medium; sensor networks; Non linear phenomenon; discrete time-varying systems; Finite horizon; Time varying system; successive packet dropouts; Sufficient condition; Simulation; Linear matrix inequality; Recursive method; Signal processing; Independent set; randomly varying nonlinearities; Non linear effect; Sensor array; Signal detection
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2012.2190599

This paper is concerned with the distributed finite-horizon filtering problem for a class of time-varying systems over lossy sensor networks. The time-varying system (target plant) is subject to randomly varying nonlinearities (RVNs) caused by environmental circumstances. The lossy sensor network suffers from quantization errors and successive packet dropouts that are described in a unified framework. Two mutually independent sets of Bernoulli distributed white sequences are introduced to govern the random occurrences of the RVNs and successive packet dropouts. Through available output measurements from not only the individual sensor but also its neighboring sensors according to the given topology, a sufficient condition is established for the desired distributed finite-horizon filter to ensure that the prescribed average filtering performance constraint is satisfied. The solution of the distributed filter gains is characterized by solving a set of recursive linear matrix inequalities. A simulation example is provided to show the effectiveness of the proposed filtering scheme.