A Robust Direct Position Determination Method Based on Block Sparse Bayesian Learning in the Presence of Unknown Mutual Coupling

Qianyuan Shi, Yuexian Wang, Chuang Han, Rongfeng Li, Chengyan He, Ling Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a block sparse Bayesian learning (BSBL) based robust direct position determination (DPD) method is proposed for locating multiple emitters in the presence of unknown mutual coupling in distributed sensor arrays. This method initiates by conducting a matrix transformation on the actual steering vector, effectively segregating the position parameter from the mutual coupling coefficient. Besides, the BSBL algorithm is designed to iteratively update the hyperparameters. Ultimately, the position of the radio emitter is estimated based on the mean value of the posterior distribution derived from the reconstruction process. At the same time, a mutual coupling coefficient estimator is provided based on the principle of subspace, which can achieve more accurate localization by compensating the mutual coupling coefficient in the sparse dictionary. Simulation results verify that the developed BSBL scheme outperforms the state-of-the-art solution in terms of localization accuracy and robustness to unknown mutual coupling.

Original languageEnglish
Title of host publicationProceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350316728
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023 - Zhengzhou, Henan, China
Duration: 14 Nov 202317 Nov 2023

Publication series

NameProceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023

Conference

Conference2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
Country/TerritoryChina
CityZhengzhou, Henan
Period14/11/2317/11/23

Keywords

  • block sparse Bayesian learning
  • direct position determination
  • mutual coupling
  • radio emitters

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