XIAO Shuo, LI Tianxu, TANG Chaogang, CAO Yuan. Coverage Adaptive Optimization Algorithm of Static-Sensor Networks for Target Discovery[J]. Chinese Journal of Electronics, 2019, 28(2): 398-403. doi: 10.1049/cje.2018.02.009
Citation: XIAO Shuo, LI Tianxu, TANG Chaogang, CAO Yuan. Coverage Adaptive Optimization Algorithm of Static-Sensor Networks for Target Discovery[J]. Chinese Journal of Electronics, 2019, 28(2): 398-403. doi: 10.1049/cje.2018.02.009

Coverage Adaptive Optimization Algorithm of Static-Sensor Networks for Target Discovery

doi: 10.1049/cje.2018.02.009
Funds:  This work is supported by the Natural Science Foundation of Jiangsu Province (No.BK20150193, No.BK20150201) and the National Natural Science Foundation of China (No.U1534208).
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  • Corresponding author: CAO Yuan (corresponding author)received his B.S. degree in Electric Engineering and Automation from Dalian Jiaotong University and Ph.D. degree in Traffic Information Engineering and Control from Beijing Jiaotong University in 2004 and 2011 respectively, where he is now an associate professor. Since 2006, he has participated in many engineering practice, especially in the signal and communication system of high-speed railway. He has taken part in several key national research projects in the field of high-speed train control system. His research interests include fault diagnosis in train control systems. (Email:ycao@bjtu.edu.cn)
  • Received Date: 2017-06-19
  • Rev Recd Date: 2017-08-02
  • Publish Date: 2019-03-10
  • Sensor networks contain a large number of nodes that can perceive changes of external environment, which makes sensor networks particularly suitable for target tracking and discovery. In practical applications, once the sensor nodes are arranged, it is difficult to move them. We focus on analysing the target discovery ability of static-sensor networks. We divided the target into two kinds, one is persistent target and the other is instantaneous target. We investigate target discovery probability and discovery delay with different nodes density, sensing range and duty cycle. Energy saving is still the most important problem for the applications of sensor networks. Balancing target discovery capability and lifetime of the whole sensor network is necessary. Based on the theoretical analysis, we propose a coverage adaptive optimization algorithm that significantly prolongs the life of sensor networks. Simulation results show the advantage of coverage adaptive optimization algorithm over previous proposed methods.
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