Journal ArticleDOI
On robust Capon beamforming and diagonal loading
TLDR
It is shown that a natural extension of the Capon beamformer to the case of uncertain steering vectors also belongs to the class of diagonal loading approaches, but the amount of diagonalloading can be precisely calculated based on the uncertainty set of the steering vector.Abstract:
The Capon (1969) beamformer has better resolution and much better interference rejection capability than the standard (data-independent) beamformer, provided that the array steering vector corresponding to the signal of interest (SOI) is accurately known. However, whenever the knowledge of the SOI steering vector is imprecise (as is often the case in practice), the performance of the Capon beamformer may become worse than that of the standard beamformer. Diagonal loading (including its extended versions) has been a popular approach to improve the robustness of the Capon beamformer. We show that a natural extension of the Capon beamformer to the case of uncertain steering vectors also belongs to the class of diagonal loading approaches, but the amount of diagonal loading can be precisely calculated based on the uncertainty set of the steering vector. The proposed robust Capon beamformer can be efficiently computed at a comparable cost with that of the standard Capon beamformer. Its excellent performance for SOI power estimation is demonstrated via a number of numerical examples.read more
Citations
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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.
Journal ArticleDOI
A sparse signal reconstruction perspective for source localization with sensor arrays
TL;DR: This work presents a source localization method based on a sparse representation of sensor measurements with an overcomplete basis composed of samples from the array manifold that has a number of advantages over other source localization techniques, including increased resolution, improved robustness to noise, limitations in data quantity, and correlation of the sources.
Journal ArticleDOI
Robust minimum variance beamforming
R.G. Lorenz,Stephen Boyd +1 more
TL;DR: An extension of minimum variance beamforming that explicitly takes into account variation or uncertainty in the array response, via an ellipsoid that gives the possible values of the array for a particular look direction is introduced.
Journal ArticleDOI
Convex Optimization-Based Beamforming
Alex B. Gershman,Nicholas D. Sidiropoulos,Shahram Shahbazpanahi,Mats Bengtsson,Bjorn Ottersten +4 more
TL;DR: It is demonstrated that convex optimization provides an indispensable set of tools for beamforming, enabling rigorous formulation and effective solution of both long-standing and emerging design problems.
Journal ArticleDOI
Source Localization and Sensing: A Nonparametric Iterative Adaptive Approach Based on Weighted Least Squares
TL;DR: This paper presents a nonparametric and hyperparameter, free-weighted, least squares-based iterative adaptive approach for amplitude and phase estimation (IAA-APES) in array processing and shows that further improvements in resolution and accuracy can be achieved by applying the parametric relaxation-based cyclic approach (RELAX).
References
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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.
Journal ArticleDOI
High-resolution frequency-wavenumber spectrum analysis
TL;DR: In this article, a high-resolution frequency-wavenumber power spectral density estimation method was proposed, which employs a wavenumber window whose shape changes and is a function of the wave height at which an estimate is obtained.
Book
Nonlinear Programming: Sequential Unconstrained Minimization Techniques
TL;DR: This report gives the most comprehensive and detailed treatment to date of some of the most powerful mathematical programming techniques currently known--sequential unconstrained methods for constrained minimization problems in Euclidean n-space--giving many new results not published elsewhere.
Journal ArticleDOI
An algorithm for linearly constrained adaptive array processing
TL;DR: A constrained least mean-squares algorithm has been derived which is capable of adjusting an array of sensors in real time to respond to a signal coming from a desired direction while discriminating against noises coming from other directions.
Journal ArticleDOI
Applications of second-order cone programming
TL;DR: In this paper, an efficient primal-dual interior-point method for solving second-order cone programs (SOCP) is presented. But it is not a generalization of interior point methods for convex problems.