Mobility-Aided Wireless Sensor Network Localization via Semidefinite Programming

Soheil Salari

doi:10.1109/TWC.2013.110813.120379

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Mobility-Aided Wireless Sensor Network Localization via Semidefinite Programming

2013-12-01

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Soheil Salari *

Shahram Shahbazpanahi

Kemal Özdemir

DOI：10.1109/TWC.2013.110813.120379

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Abstract

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In this paper, considering a mobile wireless sensor network, we study the problem of exploiting sensor mobility information in the process of sensor localization under two range measurement models, namely the time-of-arrival (TOA) model and the received signal strength (RSS) model. To do so, for each model, we first derive the maximum likelihood (ML) location estimator for the case of error-free velocity measurements. As the corresponding optimization problems are non-convex, we resort to semi-definite relaxation (SDR) techniques to find approximate solutions to each problem using semi-definite programming (SDP). We then extend our results to the cases where the velocity measurements are subject to measurement errors. Our simulation results show that exploiting the mobility information in the localization process can significantly improve the performance of the sensor localization. Moreover, mobility-aided localization has the potential to address some of typical positioning problems, such as sensitivity to the ranging measurement errors and the requirement on the number of the anchors needed to uniquely localize the sensor nodes.

Keywords:

Sensor localization

mobile sensor networks

semi-definite programming

convex programming

semi-definite relaxation

mobile localization

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