Please use this identifier to cite or link to this item: http://hdl.handle.net/11144/3648
Title: Distributed Algorithm for Target Localization in Wireless Sensor Networks Using RSS and AoA Measurements
Authors: Tomic, Slavisa
Beko, Marko
Dinis, Rui
Carvalho, Paulo Montemuza
Keywords: Wireless Localization
Wireless Sensor network (WSN)
Received Signal Strength (RSS)
Angle-of-arrival (AoA)
Second-Order Cone Programming (SOCP)
Generalized Trust Region Sub-Problem (GTRS)
Issue Date: 2016
Publisher: Elsevier
Citation: S. Tomic, M.B, Beko, R. Dinis, P. Carvalho, Distributed Algorithm for Target Localization in Wireless Sensor Networks Using RSS and AoA Measurements, Elsevier Pervasive and Mobile Computing, Vol. 2017, No. 37, pp. 63 - 77, October, 2016
Abstract: This paper addresses target localization problem in a cooperative 3-D wireless sensor network (WSN). We employ a hybrid system that fuses distance and angle measurements, extracted from the received signal strength (RSS) and angle-of-arrival (AoA) information, respectively. Based on range measurement model and simple geometry, we derive a novel non-convex estimator based on the least squares (LS) criterion. The derived non-convex estimator tightly approximates the maximum likelihood (ML) one for small noise levels. We show that the developed non-convex estimator is suitable for distributed implementation, and that it can be transformed into a convex one by applying a second-order cone programming (SOCP) relaxation technique. We also show that the developed non-convex estimator can be transformed into a generalized trust region sub-problem (GTRS) framework, by following the squared range (SR) approach. The proposed SOCP algorithm for known transmit powers is then generalized to the case where the transmit powers are different and not known. Furthermore, we provide a detailed analysis of the computational complexity of the proposed algorithms. Our simulation results show that the new estimators have excellent performance in terms of the estimation accuracy and convergence, and they confirm the effectiveness of combining two radio measurements.
Peer reviewed: yes
URI: http://hdl.handle.net/11144/3648
metadata.dc.identifier.doi: 10.1016/j.pmcj.2016.09.013
ISSN: 1574-1192
Publisher version: https://www.sciencedirect.com/science/article/pii/S157411921630236X
Appears in Collections:DCT - Artigos/Papers

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