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Sensors 2016, 16(1), 29;

Energy Efficient Moving Target Tracking in Wireless Sensor Networks

1,2,* and 1,2
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang 110179, China
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 15 September 2015 / Revised: 10 December 2015 / Accepted: 21 December 2015 / Published: 2 January 2016
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Moving target tracking in wireless sensor networks is of paramount importance. This paper considers the problem of state estimation for L-sensor linear dynamic systems. Firstly, the paper establishes the fuzzy model for measurement condition estimation. Then, Generalized Kalman Filter design is performed to incorporate the novel neighborhood function and the target motion information, improving with an increasing number of active sensors. The proposed measurement selection approach has some advantages in time cost. As such, if the desired accuracy has been achieved, the parameter initialization for optimization can be readily resolved, which maximizes the expected lifespan while preserving tracking accuracy. Through theoretical justifications and empirical studies, we demonstrate that the proposed scheme achieves substantially superior performances over conventional methods in terms of moving target tracking under the resource-constrained wireless sensor networks. View Full-Text
Keywords: wireless sensor networks; target tracking; generalized Kalman filter; neighborhood function; fuzzy wireless sensor networks; target tracking; generalized Kalman filter; neighborhood function; fuzzy

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Wen, Y.; Gao, R.; Zhao, H. Energy Efficient Moving Target Tracking in Wireless Sensor Networks. Sensors 2016, 16, 29.

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