SPICE: A Sparse Covariance-Based Estimation Method for Array Processing

2010/11/10 by Petre Stoica, Prabhu Babu, Jian Li · 9 citations
Computer Science · Engineering · #Direction-of-Arrival Estimation Techniques #Structural Health Monitoring Techniques #Speech and Audio Processing

paper · doi:10.1109/tsp.2010.2090525

Abstract

This paper presents a novel SParse Iterative Covariance-based Estimation approach, abbreviated as SPICE, to array processing. The proposed approach is obtained by the minimization of a covariance matrix fitting criterion and is particularly useful in many-snapshot cases but can be used even in single-snapshot situations. SPICE has several unique features not shared by other sparse estimation methods: it has a simple and sound statistical foundation, it takes account of the noise in the data in a natural manner, it does not require the user to make any difficult selection of hyperparameters, and yet it has global convergence properties.

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