New two-step semidefinite relaxation method for acoustic energy-based localization

被引：0
|
作者：
Tian Q. [1 ]
Feng D. [1 ]
Li J. [2 ]
Hu H. [1 ]
机构：
[1] National Key Lab. of Radar Signal Processing, Xidian University, Xi'an
[2] State Key Lab. of Integrated Service Networks, Xidian University, Xi'an
来源：
Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University | 2019年 / 46卷 / 04期
关键词：
Acoustic energy; Semidefinite programming; Source localization; Weighted leasts quares; Wireless sensor networks;
D O I：
10.19665/j.issn1001-2400.2019.04.003
中图分类号：
学科分类号：
摘要：
A new two-step semidefinite relaxation method is proposed to deal with the nonlinear and non-convex problem of acoustic energy-based localization in wireless sensor networks. The proposed algorithm transforms the nonlinear positioning equations into a weighted least squares estimation problem of the unknown source location and signal transmit power, which is then solved in two steps. First, the signal transmit power is eliminated from the cost function by expressing it as a function of the source position in the least square sense. In the second step, the weighted least squares formulation is converted into a semidefinite programming(SDP) optimization problem by using a new convex relaxation technique. The tightness of the semidefinite relaxation method is theoretically proved. Simulation results indicate that compared with the previous methods, the proposed algorithm has a higher localization accuracy, especially when the measurement error is relatively large. © 2019, The Editorial Board of Journal of Xidian University. All right reserved.
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页码：16 / 21and42
页数：2126
相关论文
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