TY - GEN
T1 - A WLS estimator for target localization in a cooperative wireless sensor network
AU - Tomic, Slavisa
AU - Beko, Marko
AU - Dinis, Rui
AU - Tuba, Milan
N1 - Sem pdf conforme despacho.
Fundação para a Ciência e a Tecnologia under Projects PEst-OE/EEI/UI0066/2014, and PEst-OE/EEI/LA0008/2013 (IT pluriannual founding and HETNET), PEst-OE/EEI/UI0066/2011 (UNINOVA pluriannual founding), ADIN PTDC/EEI-TEL/2990/2012, COPWIN PTDC/EEI-TEL/1417/2012 and PTDC/EEITEL/6308/2014-HAMLeT, as well as the grants SFRH/BPD/108232/2015, SFRH/BD/91126/2012 and Ciência 2008 Post-Doctoral Research grant.
PY - 2016
Y1 - 2016
N2 - This paper addresses target localization problem in a cooperative 3-D wireless sensor network (WSN). We employ non-traditional methodology which merges distance and angle measurements, respectively withdrawn from the received signal strength (RSS) and angle-of-arrival (AoA) information. Based on RSS measurement model and effortless geometry, a novel non-convex estimator according to the weighted least squares (WLS) criterion is obtained, which closely approximates the maximum likelihood (ML) estimator for small noise. It is shown that the devised estimator is appropriate for distributed implementation. Following the squared range (SR) approach, we propose a suboptimal SR-WLS estimator according to the generalized trust region sub-problem (GTRS) framework, to estimate the locations of all targets in the WSN. According to our simulations, the new estimator has excellent performance in a great variety of considered settings, in which the effectiveness of fusing two radio measurements is confirmed.
AB - This paper addresses target localization problem in a cooperative 3-D wireless sensor network (WSN). We employ non-traditional methodology which merges distance and angle measurements, respectively withdrawn from the received signal strength (RSS) and angle-of-arrival (AoA) information. Based on RSS measurement model and effortless geometry, a novel non-convex estimator according to the weighted least squares (WLS) criterion is obtained, which closely approximates the maximum likelihood (ML) estimator for small noise. It is shown that the devised estimator is appropriate for distributed implementation. Following the squared range (SR) approach, we propose a suboptimal SR-WLS estimator according to the generalized trust region sub-problem (GTRS) framework, to estimate the locations of all targets in the WSN. According to our simulations, the new estimator has excellent performance in a great variety of considered settings, in which the effectiveness of fusing two radio measurements is confirmed.
KW - Angle-of-arrival (AoA)
KW - Generalized trust region sub-problem (GTRS)
KW - Received signal strength (RSS)
KW - Wireless sensor network (WSN)
UR - http://www.scopus.com/inward/record.url?scp=84962050555&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-31165-4_27
DO - 10.1007/978-3-319-31165-4_27
M3 - Conference contribution
AN - SCOPUS:84962050555
SN - 978-3-319-31164-7
VL - 470
T3 - IFIP Advances in Information and Communication Technology
SP - 273
EP - 283
BT - Technological Innovation for Cyber-Physical Systems - 7th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2016, Proceedings
PB - Springer New York LLC
T2 - 7th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2016
Y2 - 11 April 2016 through 13 April 2016
ER -