Journal ArticleDOI
SPICE: A Sparse Covariance-Based Estimation Method for Array Processing
Petre Stoica,Prabhu Babu,Jian Li +2 more
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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
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Proceedings ArticleDOI
Direction-of-arrival estimation using sparse variable projection optimization
TL;DR: A new low complexity direction-of-arrival (DOA) estimation method based on sparse variable projection (SVP) optimization that estimates an indicative sparse vector that indicates the locations of DOA from each visual sources corresponding to DOA sampling space is proposed.
Journal ArticleDOI
The Multi-Level Dilated Nested Array for Direction of Arrival Estimation
Yan Zhou,Yanyan Li,Cai Wen +2 more
TL;DR: The proposed multi-level DNA can detect more sources and achieve more accurate estimation performance compared with the original DNA, and the corresponding DOA Cramér-Rao bound, which gives the low bound on the variance of estimated DOA, is deduced in detail.
Posted Content
A Simultaneous Sparse Approximation Method for Multidimensional Harmonic Retrieval
TL;DR: In this paper, a sparse-based method for the estimation of the parameters of multidimensional modal (harmonic or damped) complex signals in noise is presented, which does not require an association step since the estimated modes are automatically "paired".
Journal ArticleDOI
Altitude measurement of low-angle target in complex terrain for very high-frequency radar
Yisong Zheng,Baixiao Chen +1 more
TL;DR: A new perturbational multipath signal model is proposed, where perturbation caused by complex terrain is considered as the gain and phase errors of the steering vector of the multipATH signal.
Journal ArticleDOI
DOA and power estimation using a sparse representation of second-order statistics vector and ℓ 0 -norm approximation
TL;DR: Numerical simulations show that the proposed reconstruction algorithm not only has high resolution and good robustness to noise, but also provides an almost unbiased power estimation.
References
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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.
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