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GLOBECOM
2009
IEEE

Received Signal Strength-Based Wireless Localization via Semidefinite Programming

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Received Signal Strength-Based Wireless Localization via Semidefinite Programming
The received signal strength (RSS)-based approach to wireless localization offers the advantage of low cost and easy implementability. To circumvent the nonconvexity of the conventional maximum likelihood (ML) estimator, in this paper, we propose convex estimators specifically for the RSS-based localization problems. Both noncooperative and cooperative schemes are considered. We start with the noncooperative RSS-based localization problem and derive a nonconvex estimator that approximates the ML estimator but has no logarithm in the residual. Next, we apply the semidefinite relaxation technique to the derived nonconvex estimator and develop a convex estimator. To further improve the estimation performance, we append the ML estimator to the convex estimator with the result by the convex estimator as the initial point. We then extend these techniques to the cooperative localization problem. The corresponding Cramer
Wentao Robin Ouyang, Albert Kai-Sun Wong, Chin-Tau
Added 18 Feb 2011
Updated 18 Feb 2011
Type Journal
Year 2009
Where GLOBECOM
Authors Wentao Robin Ouyang, Albert Kai-Sun Wong, Chin-Tau A. Lea, Victoria Ying Zhang
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