Title
Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks.
Abstract
The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods.
Year
DOI
Venue
2018
10.3390/s18051646
SENSORS
Keywords
Field
DocType
sensor self-localization,source localization,sensor networks,convex optimization,semidefinite programming
Minimax,Algorithm,Electronic engineering,Engineering,Wireless sensor network,Convex optimization,Optimization problem,Semidefinite programming,Acoustic source localization,Estimator,Computation
Journal
Volume
Issue
Citations 
18
5.0
0
PageRank 
References 
Authors
0.34
28
5
Name
Order
Citations
PageRank
Y.S. Yong1344.90
Haiyan Wang232.10
Xiao-Hong Shen33213.95
Bing Leng4185.21
Shuangquan Li500.34