In this work, the estimation of the Directions of Arrival (DOAs) of multiple source signals from a single observation vector is considered. In particular, the estimation, detection and super-resolution performance of three algorithms based on the theory of Compressed Sensing (the classical l1-minimization or LASSO, the fast smooth l0-minimization, and the SPICE algorithm) are analyzed and compared with the classical Fourier beamformer. This comparison is carried out using both simulated data and real sonar data.
Three CS-based beamformers for single snapshot DOA estimation
FORTUNATI, STEFANO;GINI, FULVIO;GRECO, MARIA;
2014-01-01
Abstract
In this work, the estimation of the Directions of Arrival (DOAs) of multiple source signals from a single observation vector is considered. In particular, the estimation, detection and super-resolution performance of three algorithms based on the theory of Compressed Sensing (the classical l1-minimization or LASSO, the fast smooth l0-minimization, and the SPICE algorithm) are analyzed and compared with the classical Fourier beamformer. This comparison is carried out using both simulated data and real sonar data.File in questo prodotto:
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