Fast implementation of sparse iterative covariance-based estimation for array processing
- 1 November 2011
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 7 (10586393) , 2031-2035
- https://doi.org/10.1109/acssc.2011.6190383
Abstract
Fast implementations of the SParse Iterative Covariance-based Estimation (SPICE) algorithm are presented for source localization in passive sonar applications. SPICE is a robust, user parameter-free, high-resolution, iterative and globally convergent estimation algorithm for array processing. SPICE offers superior resolution and lower sidelobe levels for source localization at the cost of a higher computational complexity compared to the conventional delay-and-sum beamforming method. It is shown in this paper that the computational complexity of the SPICE algorithm can be reduced by exploiting the Toeplitz structure of the array output covariance matrix using the Gohberg-Semencul factorization. The fast implementations for both the hydrophone uniform linear array (ULA) and the vector-sensor ULA scenarios are proposed and the computational gains are illustrated by numerical simulations.Keywords
This publication has 15 references indexed in Scilit:
- Fast implementation of sparse iterative covariance-based estimation for source localizationThe Journal of the Acoustical Society of America, 2012
- SPICE: A Sparse Covariance-Based Estimation Method for Array ProcessingIEEE Transactions on Signal Processing, 2010
- New Method of Sparse Parameter Estimation in Separable Models and Its Use for Spectral Analysis of Irregularly Sampled DataIEEE Transactions on Signal Processing, 2010
- Acoustic vector-sensor beamforming and Capon direction estimationIEEE Transactions on Signal Processing, 1998
- Matrix Algebra From a Statistician’s PerspectivePublished by Springer Nature ,1997
- Acoustic vector-sensor array processingIEEE Transactions on Signal Processing, 1994
- Efficient inversion of Toeplitz-block Toeplitz matrixIEEE Transactions on Acoustics, Speech, and Signal Processing, 1983
- An efficient algorithm for a large Toeplitz set of linear equationsIEEE Transactions on Acoustics, Speech, and Signal Processing, 1979
- Block Toeplitz Matrix InversionSIAM Journal on Applied Mathematics, 1973
- Toeplitz Matrix Inversion: The Algorithm of W. F. TrenchJournal of the ACM, 1969