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
Guaranteed Localization of More Sources Than Sensors With Finite Snapshots in Multiple Measurement Vector Models Using Difference Co-Arrays
Heng Qiao,Piya Pal +1 more
TL;DR: This paper develops uniform upper bounds on the estimation error that is obeyed by any algorithm belonging to this family of correlation-aware optimization problems, and establishes rigorous probabilistic support recovery guarantees in the regime.
Journal ArticleDOI
Grid Evolution Method for DOA Estimation
TL;DR: A grid evolution direction of arrival (GEDOA) estimation method that makes the grid nonuniformly evolve from coarse to dense and has better computational efficiency and better resolution and lower MSE at relative high SNR.
Proceedings ArticleDOI
A compact formulation for the l21 mixed-norm minimization problem
TL;DR: For the special case of uniform linear sampling, this work presents an extension of the compact formulation for gridless parameter estimation by means of semidefinite programming, and derives in this case from the compact problem formulation the exact equivalence between the ℓ2,1 mixed- norm minimization and the atomic-norm minimization.
Journal ArticleDOI
Sparse Bayesian learning for off-grid DOA estimation with nested arrays
TL;DR: A new data model formulation is presented, in which the noise variance is taken as a part of the unknown signal of interest, so as to learn its value by the Bayesian inference inherently.
Journal ArticleDOI
Tyler's Covariance Matrix Estimator in Elliptical Models With Convex Structure
Ilya Soloveychik,Ami Wiesel +1 more
TL;DR: This work proposes a new COCA estimator-a convex relaxation which can be efficiently solved and proves that the relaxation is tight in the unconstrained case for a finite number of samples, and in the constrained case asymptotically.
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