Consensus Estimation Based Underwater Target Tracking with Acoustic Sensor Networks

Acoustic sensor networks (ASNs) have been identified as a promising technology to monitor and explore the underwater resources. Most applications of ASNs are required to track an underwater target in an accurate and efficient manner. However, the resource-constrained characteristics on acoustic communication makes it challenging to achieve the tracking task. In this paper, we are concerned with underwater target tracking problem for ASNs, where underwater sensor nodes are used to detect and acquire the position information of underwater target. Then, a consensus estimation based tracking algorithm is proposed for ASNs, such that the negative effect of noises in underwater target and sensors can be reduced. Based on the prediction states of target, a duty-cycle strategy is proposed to improve energy efficiency. In addition, the asymptotic unbiasedness of the estimation based tracking algorithm is analysed in the presence of measurement and communication noises. Finally, simulation results are performed to show the effectiveness of the proposed method.