Consensus Based Estimation Over Relay Assisted Sensor Networks for Situation Monitoring

This paper focuses on exploiting the sensor fusion capability for situation monitoring applications over a kind of relay assisted sensor networks consisting of multiple kinds of sensor nodes (SNs) and relay nodes (RNs). SNs implement assimilation of new measurement and cooperation with other nodes. Moreover, SNs have different sensing modalities, which can only measure a part of target parameter vector for situation monitoring. While for RNs, the main role is to aggregate their neighboring data. We propose a distributed consensus based unbiased estimation algorithm for this kind of relay assisted sensor networks. By using algebraic graph theory in conjunction with Markov chain approach, we demonstrate how the distributed estimation method can be transformed to circumvent the challenges arisen from the heterogeneity of different kinds of nodes. We analyze the performance of asymptotic unbiasedness and consistency of the proposed algorithm in the presence of asymmetric communication, i.e., when a node can receive information from another node but not vice versa. Furthermore, a quantitative bound on the rate of convergence of the proposed algorithm in the almost sure sense is explicitly established. Finally, simulation results are provided to validate the effectiveness of the proposed algorithm.