Quantized Filtering Schemes for Multi-Sensor Linear State Estimation: Stability and Performance Under High Rate Quantization

In this paper we consider state estimation of a discrete time linear system using multiple sensors, where the sensors quantize their individual innovations, which are then combined at the fusion center to form a global state estimate. We prove the stability of the estimation scheme under sufficientl...

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Vydané v:	IEEE transactions on signal processing Ročník 61; číslo 15; s. 3852 - 3865
Hlavní autori:	Leong, Alex S., Dey, Subhrakanti, Nair, Girish N.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, NY IEEE 01.08.2013 Institute of Electrical and Electronics Engineers
Predmet:	Applied sciences Asymptotic stability Detection, estimation, filtering, equalization, prediction Electrical Engineering with specialization in Signal Processing Elektroteknik med inriktning mot signalbehandling Exact sciences and technology Filtering Information, signal and communications theory Kalman filtering Numerical stability quantization Quantization (signal) Sampling, quantization Sensor fusion sensor networks Sensor systems Sensors Signal and communications theory Signal, noise stability Stability analysis State estimation Technological innovation Telecommunications and information theory Performance evaluation Parameter estimation Resource allocation sensor networks Innovation Covariance Optimal allocation Signal quantization Kalman filtering High bit rate Linear estimation State estimation Signal detection stability High rate transmission quantization Multisensor Discrete time systems Measurement sensor Covariance matrix Signal processing Approximation error Numerical simulation Asymptotic approximation Resource management Sensor array
ISSN:	1053-587X, 1941-0476, 1941-0476
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Popis
Shrnutí:	In this paper we consider state estimation of a discrete time linear system using multiple sensors, where the sensors quantize their individual innovations, which are then combined at the fusion center to form a global state estimate. We prove the stability of the estimation scheme under sufficiently high bit rates. We obtain asymptotic approximations for the error covariance matrix that relates the system parameters and quantization levels used by the different sensors. Numerical results show close agreement with the true error covariance for quantization at high rates. An optimal rate allocation problem amongst the different sensors is also considered.
ISSN:	1053-587X 1941-0476 1941-0476
DOI:	10.1109/TSP.2013.2264465