NDLI: Cooperative localization in wireless sensor networks using combined measurements

Content Provider	IEEE Xplore Digital Library
Author	Tomic, S. Beko, M. Dinis, R. Berbakov, L.
Copyright Year	2015
Description	Author affiliation: LARSyS, Univ. de Lisboa, Lisbon, Portugal (Tomic, S.) \|\| Mihailo Pupin Inst., Univ. of Belgrade, Belgrade, Serbia (Berbakov, L.) \|\| Inst. de Telecomunicajoes, Lisbon, Portugal (Dinis, R.) \|\| Univ. Lusofona de Humanidades e Tecnol., Lisbon, Portugal (Beko, M.)
Abstract	This paper addresses node localization problem in a cooperative 3-D wireless sensor network (WSN), for both cases of known and unknown node transmit power, $P_{T}.$ We employ a hybrid system that combines distance and angle measurements, extracted from the received signal strength (RSS) and angle-of-arrival (AoA) information, respectively. Based on RSS measurement model and simple geometry, we derive a novel non-convex estimator based on the least squares (LS) criterion, which tightly approximates the maximum likelihood (ML) estimator for small noise. It is shown that the developed estimator can be transformed into a convex one by applying appropriate semidefinite programming (SDP) relaxation technique. Moreover, we show that the generalization of the proposed estimator for known $P_{T}$ is straightforward to the case where $P_{T}$ is not known. Our simulation results show that the new estimator has excellent performance in a great variety of considered scenarios, and is robust to not knowing $P_{T}.$
Starting Page	488
Ending Page	491
File Size	501423
Page Count	4
File Format	PDF
e-ISBN	9781509000555
DOI	10.1109/TELFOR.2015.7377513
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-24
Publisher Place	Serbia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Geometry Wireless sensor networks Maximum likelihood estimation Least squares approximations Cooperative localization Received signal strength (RSS) Angle-of-arrival (AoA) Convex functions Data mining Semidefinite programming (SDP) Optimization
Content Type	Text
Resource Type	Article

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