Title
Tdoa-Based Source Collaborative Localization Via Semidefinite Relaxation In Sensor Networks
Abstract
The time delay of arrival- (TDOA-) based source localization using a wireless sensor network has been considered in this paper. The maximum likelihood estimate (MLE) is formulated by taking the correlated TDOA noise into account, which is caused by the difference with the TOA of the reference sensor. The global optimal solution is difficult to obtain due to the nonconvex nature of the ML function. We propose an alternative semidefinite programming method, which transforms the original ML problem into a convex one by relaxing nonconvex equalities into convex matrix inequalities. In addition, the source localization algorithm in the presence of sensor location errors and non-line-of-sight (NLOS) observations is developed. Our simulation results demonstrate the potential advantages of the proposed method. Furthermore, the proposed source localization algorithm by taking the NLOS TOA measurements as the constraints of the convex problem can provide a good estimate.
Year
DOI
Venue
2015
10.1155/2015/248970
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
Field
DocType
Volume
Non-line-of-sight propagation,Mathematical optimization,Computer science,Matrix (mathematics),Maximum likelihood,Regular polygon,Multilateration,Wireless sensor network,Convex optimization,Semidefinite programming
Journal
11
ISSN
Citations 
PageRank 
1550-1477
5
0.50
References 
Authors
40
5
Name
Order
Citations
PageRank
Y.S. Yong1344.90
Haiyan Wang23916.48
Xiao-Hong Shen3165.10
Ke He4285.82
Xionghu Zhong515214.61