Measurement Information Consensus Based Distributed Estimation of Unknown Source by Using Mobile Sensor Networks

This paper addresses the problem of estimating unknown environment spatial source fields by using the measured information from mobile sensor networks. We propose distributed estimation and control methods for sensor networks by only using local interactions. The proposed algorithm consists of two parts. Firstly, each sensor fuses from its own and its neighbor’s measurement value, then a consensus algorithm is executed by each sensor to process the fused measurement information in a distributed manner to seek the balanced measurements of the unknown source; Secondly, each mobile sensor keeps its estimate of the source by inputting the balanced measurements to a local least square estimator. To improve the performance of the estimation, a gradient descent control law was introduced to the moving sensors. Each sensor moves towards the direction of deducing the uncertainty represented by the variance matrix. Simulations are performed to investigate the effectiveness of the algorithm.