Sequential source localisation and range estimation based on shrinkage algorithm

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Sequential source localisation and range estimation based on shrinkage algorithm

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© The Institution of Engineering and Technology
Received 13/12/2016, Accepted 12/09/2017, Revised 15/06/2017, Published 15/09/2017

This study presents the shrinkage-based sequential source localisation and range estimation algorithms. The shrinkage factor is found using the variance of the estimate in the existing shrinkage algorithm. However, the variance of the estimate is difficult to calculate when the form of the estimate is complex. To circumvent this problem, the authors propose a shrinkage algorithm that employs the Cramér–Rao lower bound (CRLB) instead of the variance for the maximum likelihood (ML) estimate. The variance of the ML estimate and CRLB were found to be similar in simulation results. Furthermore, Stein's unbiased risk estimator and Ledoit–Wolf methods are used to determine the shrinkage factor. The resulting estimation accuracy of the proposed shrinkage-based sequential source localisation and range estimation methods was similar with that of the existing shrinkage algorithm.

Inspec keywords: time-of-arrival estimation; maximum likelihood estimation

Other keywords: Stein unbiased risk estimator; maximum likelihood estimation; Ledoit-Wolf method; Cramer-Rao lower bound estimation; shrinkage-based sequential source localisation and range estimation algorithm; CRLB estimation; shrinkage factor; ML estimation

Subjects: Other topics in statistics; Other topics in statistics; Signal processing theory; Signal processing and detection

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