Literature DB >> 29960432

Statistics on noise covariance matrix for covariance fitting-based compressive sensing direction-of-arrival estimation algorithm: For use with optimization via regularization.

Ji Woong Paik1, Wooyoung Hong2, Jae-Kyun Ahn3, Joon-Ho Lee1.   

Abstract

A covariance fitting algorithm for the estimation of direction-of-arrivals of multiple incident signals is addressed in this paper. The scheme takes advantage of the fact that the incident signals are spatially sparse. A previous study has presented the regularization parameters of the covariance fitting for a very large number of snapshots. In this paper, a strategy on how to determine the regularization constant of the covariance fitting for a general number of snapshots is presented. The strategy essentially exploits the norm of the noise covariance matrix. The proposed algorithm has been validated via numerical simulations.

Year:  2018        PMID: 29960432     DOI: 10.1121/1.5042354

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  1 in total

1.  An Enhanced Smoothed L0-Norm Direction of Arrival Estimation Method Using Covariance Matrix.

Authors:  Ji Woong Paik; Joon-Ho Lee; Wooyoung Hong
Journal:  Sensors (Basel)       Date:  2021-06-27       Impact factor: 3.576

  1 in total

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