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TOA-Based Robust Wireless Geolocation and Cramér-Rao Lower Bound Analysis in Harsh LOS/NLOS Environments

We consider time-of-arrival based robust geolocation in harsh line-of-sight/non-line-of-sight environments. Herein, we assume the probability density function (PDF) of the measurement error to be completely unknown and develop an iterative algorithm for robust position estimation. The iterative algorithm alternates between a PDF estimation step, which approximates the exact measurement error PDF (albeit unknown) under the current parameter estimate via adaptive kernel density estimation, and a parameter estimation step, which resolves a position estimate from the approximate log-likelihood function via a quasi-Newton method. Unless the convergence condition is satisfied, the resolved position estimate is then used to refine the PDF estimation in the next iteration. We also present the best achievable geolocation accuracy in terms of the Cramér-Rao lower bound. Various simulations have been conducted in both real-world and simulated scenarios. When the number of received range measurements is large, the new proposed position estimator attains the performance of the maximum likelihood estimator (MLE). When the number of range measurements is small, it deviates from the MLE, but still outperforms several salient robust estimators in terms of geolocation accuracy, which comes at the cost of higher computational complexity.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-92694
Date January 2013
CreatorsYin, Feng, Fritsche, Carsten, Gustafsson, Fredrik, Zoubir, Abdelhak M
PublisherLinköpings universitet, Reglerteknik, Linköpings universitet, Tekniska högskolan, Linköpings universitet, Reglerteknik, Linköpings universitet, Tekniska högskolan, Technical University of Darmstadt, Germany, Technical University of Darmstadt, Germany, Institute of Electrical and Electronics Engineers (IEEE)
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeArticle in journal, info:eu-repo/semantics/article, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationIEEE Transactions on Signal Processing, 1053-587X, 2013, 61:9, s. 2243-2255

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