Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks

• Main Authors: Chih-Yu Wen, Ying-Chih Chen
• Format: Article
• Language: English
• Published: MDPI AG 2012-11-01
• Series: Sensors
• Subjects: wireless sensor networks; target tracking; Bayesian filtering; neural networking; covariance intersection
• Online Access: http://www.mdpi.com/1424-8220/12/11/15308
• ISSN: 1424-8220

This paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processingis conducted to achieve object positioning, considering a cluster-based network topology. Random timers and local information are applied to adaptively select a sub-cluster for thelocalization task. The proposed energy-efficient tracking algorithm allows each sub-clustermember to locally estimate the target position with a Bayesian filtering framework and a neural networking model, and further performs estimation fusion in the leader node with the covariance intersection algorithm. This paper evaluates the merits and trade-offs of the protocol design towards developing more efficient and practical algorithms for objectposition estimation.