Energy-efficient coverage problems in wireless ad-hoc sensor networks
Computer Communications
Universal decentralized detection in a bandwidth-constrained sensor network
IEEE Transactions on Signal Processing - Part I
Power scheduling of universal decentralized estimation in sensor networks
IEEE Transactions on Signal Processing
Decentralized Quantized Kalman Filtering With Scalable Communication Cost
IEEE Transactions on Signal Processing - Part I
Universal decentralized estimation in a bandwidth constrained sensor network
IEEE Transactions on Information Theory
Decentralized estimation in an inhomogeneous sensing environment
IEEE Transactions on Information Theory
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The problem of state estimation with quantized measurements is considered. Due to the nonlinearity of the quantizer, estimating the system state is a nonlinear and nonGaussian estimation problem even if the system is linear and Gaussian. A novel algorithm for approximate minimum mean square error (MMSE) state estimation with quantized measurements is proposed. The algorithm is based on the information extraction from the quantized measurements. Through effective information extraction from the quantized measurements, the true measurement value is reestablished approximatively. Simulation and comparison of the proposed algorithm with the existing methods by simulation of a typical tracking scenario in Wireless Sensor Networks (WSNs) systems are presented. The numerical results show that the tracking algorithm is effective.