NLOS Mitigation Using Sparsity Feature And Iterative Methods

Abbas Abolfathi; Fereidoon Behnia; Farokh Marvasti

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arXiv · 1803.06838

NLOS Mitigation Using Sparsity Feature And Iterative Methods

Abbas Abolfathi·Fereidoon Behnia·Farokh Marvasti

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Abstract

Well-known methods are employed to localize mobile station (MS) using line of sight (LOS) measurements. These methods may result in large error if they are fed with non LOS (NLOS) measurements. Our proposed algorithm, referred to as Sparse Recovery of NLOS using IMAT (SRNI), considers NLOS as unknown variables and solves the resultant underdetermined system emphasizing on its sparsity feature based on IMAT methods. Simulations are conducted to investigate the performance of SRNI in comparison of other conventional algorithms. Results demonstrate that SRNI is fast enough to deal with large combination of BSs and also accurate in lower number of BSs

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BibTeX RIS

Abbas Abolfathi, Fereidoon Behnia, Farokh Marvasti. 2018-03-19. NLOS Mitigation Using Sparsity Feature And Iterative Methods. https://arxiv.org/abs/1803.06838

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