Reduced Complexity Semidefinite Relaxation Algorithms for Source Localization Based on Time Difference of Arrival
Issue No. 09 - September (2011 vol. 10)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2010.263
Enyang Xu , University of California, Davis, Davis
Zhi Ding , University of California, Davis, Davis
Soura Dasgupta , University of Iowa, Iowa
We investigate the problem of source localization based on measuring time difference of signal arrivals (TDOA) from the source emitter. Taking into account the colored measurement noise, we adopt a min-max principle to develop two lower complexity semidefinite relaxation algorithms that can be reliably solved using semidefinite programming. The reduction of algorithm complexity is achieved through a simple, but effective method to select a reference node among participating measurement nodes such that only selective time differences of signal arrival are exploited. Our estimation methods are insensitive to the source locations and can be used either as the final location estimate or as the initial point for more traditional search algorithms.
Source localization, time difference of arrival, semidefinite programming.
Enyang Xu, Zhi Ding, Soura Dasgupta, "Reduced Complexity Semidefinite Relaxation Algorithms for Source Localization Based on Time Difference of Arrival", IEEE Transactions on Mobile Computing, vol. 10, no. , pp. 1276-1282, September 2011, doi:10.1109/TMC.2010.263