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| Received:October 25, 2010Revised:November 10, 2011 |
| 基金项目:The work was supported by the NSFC-Guangdong Joint Foundation Key Project (No. U0735003), the Oversea Cooperation Foundation (No.60828006), and the National Natural Science Foundation of China (No. 61174070). |
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| Novel sensor scheduling and energy-efficient quantization for tracking target in wireless sensor networks |
| Guiyun LIU,Bugong XU |
| (College of Automation Science and Engineering, South China University of Technology) |
| Abstract: |
| This paper focuses on sensor scheduling and information quantization issues for target tracking in wireless sensor networks (WSNs). To reduce the energy consumption of WSNs, it is essential and effective to select the next tasking sensor and quantize the WSNs data. In existing works, sensor scheduling’ goals include maximizing tracking accuracy and minimizing energy cost. In this paper, the integration of sensor scheduling and quantization technology is used to balance the tradeoff between tracking accuracy and energy consumption. The main characteristic of the proposed schemes includes a novel filtering process of scheduling scheme, and a compressed quantized algorithm for extended Kalman filter (EKF). To make the algorithms more efficient, the proposed platform employs a method of decreasing the threshold of sampling intervals to reduce the execution time of all operations. A real tracking system platform for testing the novel sensor scheduling and the quantization scheme is developed. Energy consumption and tracking accuracy of the platform under different schemes are compared finally. |
| Key words: Wireless sensor network Vector quantization Target tracking |
