A Sparse Signal Reconstruction Algorithm in Wireless Sensor Networks

Abstract

We study reconstruction of time-varying sparse signals in a wireless sensor network, where the bandwidth and energy constraints are considered severely. A novel particle filter algorithm is proposed to deal with the coarsely quantized innovation. To recover the sparse pattern of estimate by particle filter, we impose the sparsity constraint on the filter estimate by means of two methods. Simulation results demonstrate that the proposed algorithms provide performance which is comparable to that of the full information (i.e., unquantized) filtering schemes even in the case where only 1 bit is transmitted to the fusion center.