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Hybrid RSS/AOA Localization using Approximated Weighted Least Square in Wireless Sensor Networks

We present a target localization method using an approximated error covariance matrix based weighted least squares (WLS) solution, which integrates received signal strength (RSS) and angle of arrival (AOA) data for wireless sensor networks. We approximated linear WLS errors via second-order Taylor a...

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Detalles Bibliográficos
Autores principales: Kang, SeYoung, Kim, TaeHyun, Chung, WonZoo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070383/
https://www.ncbi.nlm.nih.gov/pubmed/32093207
http://dx.doi.org/10.3390/s20041159
Descripción
Sumario:We present a target localization method using an approximated error covariance matrix based weighted least squares (WLS) solution, which integrates received signal strength (RSS) and angle of arrival (AOA) data for wireless sensor networks. We approximated linear WLS errors via second-order Taylor approximation, and further approximated the error covariance matrix using a least-squares solution and the variance in measurement noise over the sensor nodes. The algorithm does not require any prior knowledge of the true target position or noise variance. Simulations validated the superior performance of our new method.