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

Sensors

Ying-Chih Chen¹ 

[1] Department of Electrical Engineering, Graduate Institute of Communication Engineering, National Chung Hsing University, Taichung 402, Taiwan; E-Mail

关键词: wireless sensor networks;    target tracking;    Bayesian filtering;    neural networking;    covariance intersection;   

DOI  :  10.3390/s121115308

来源: mdpi

【 摘 要 】

This paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processing is 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 the localization task. The proposed energy-efficient tracking algorithm allows each sub-cluster member 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 object position estimation.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.