Journal ArticleDOI
SPICE: A Sparse Covariance-Based Estimation Method for Array Processing
Petre Stoica,Prabhu Babu,Jian Li +2 more
Reads0
Chats0
TLDR
This paper presents a novel SParse Iterative Covariance-based Estimation approach, abbreviated as SPICE, to array processing, 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.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.read more
Citations
More filters
Journal ArticleDOI
Partial Dictionary Based Off-Grid DOA Estimation Using Combined Coprime and Nested Array
TL;DR: In this paper, a partial dictionary based direction of arrival (DOA) estimation method which exploits combined coprime and nested array (CCNA) is proposed to address the off-grid problem.
Journal ArticleDOI
Gridless DOA estimation based on multivariate function genetic optimisation
Meihong Pan,Gong Zhang +1 more
TL;DR: Simulation results finally demonstrate the superiority of the proposed approach in terms of DOA estimation precision and computational efficiency over the grid-based sparse reconstruction algorithm.
Book ChapterDOI
New Challenges in Covariance Estimation: Multiple Structures and Coarse Quantization
TL;DR: In this paper , the authors revisited a fundamental problem of multivariate statistics: estimating covariance matrices from finitely many independent samples based on massive multiple-input multiple-output (MIMO) systems.
References
More filters
Journal ArticleDOI
Regression Shrinkage and Selection via the Lasso
TL;DR: A new method for estimation in linear models called the lasso, which minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant, is proposed.
Journal ArticleDOI
Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones
TL;DR: This paper describes how to work with SeDuMi, an add-on for MATLAB, which lets you solve optimization problems with linear, quadratic and semidefiniteness constraints by exploiting sparsity.
Book
Interior-Point Polynomial Algorithms in Convex Programming
TL;DR: This book describes the first unified theory of polynomial-time interior-point methods, and describes several of the new algorithms described, e.g., the projective method, which have been implemented, tested on "real world" problems, and found to be extremely efficient in practice.
Book
Spectral analysis of signals
Petre Stoica,Randolph L. Moses +1 more
TL;DR: 1. Basic Concepts. 2. Nonparametric Methods. 3. Parametric Methods for Rational Spectra.
Related Papers (5)
Two decades of array signal processing research: the parametric approach
Hamid Krim,Mats Viberg +1 more