Results 51 to 60 of about 270,830 (185)
Subspace Methods for Joint Sparse Recovery [PDF]
, 2011 We propose robust and efficient algorithms for the joint sparse recovery problem in compressed sensing, which simultaneously recover the supports of jointly sparse signals from their multiple measurement vectors obtained through a common sensing matrix ...
Bresler, Yoram +2 more
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Weighted SPICE: A Unifying Approach for Hyperparameter-Free Sparse Estimation
, 2014 In this paper we present the SPICE approach for sparse parameter estimation in a framework that unifies it with other hyperparameter-free methods, namely LIKES, SLIM and IAA.
Li, Jian, Stoica, Petre, Zachariah, Dave
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Symmetric Sparse Linear Array for Active Imaging [PDF]
2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2018 Sparse sensor arrays can achieve significantly more degrees of freedom than the number of elements by leveraging the co-array, a virtual structure that arises from the far field narrowband signal model. Although several sparse array configurations have been developed for passive sensing tasks, less attention has been paid to arrays suitable for active ...
Koivunen, Visa, Rajamaki, Robin
openaire +2 more sources
Design of large aperture sparse array for mainlobe interference cancellation
The Journal of Engineering, 2019 Large aperture sparse array has the ability of mainlobe interference suppression. However, sparse array causes grating lobe problem. If the array is steering at the target and the mainlobe interference is located at the grating lobe, the adaptive filter ...
Honggang Zhang +3 more
doaj +1 more source
Micromachines, 2022 Sparse antenna arrays based on subarrays have more and more broad application prospects for the limitation of array space, real-time algorithm and hardware costs.
Jian Yang +3 more
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Efficient computation of Hamiltonian matrix elements between non-orthogonal Slater determinants [PDF]
, 2012 We present an efficient numerical method for computing Hamiltonian matrix elements between non-orthogonal Slater determinants, focusing on the most time-consuming component of the calculation that involves a sparse array.
Bender +28 more
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An optimized 2D-Robust Adaptive Beamforming algorithm based on Matrix Completion in sparse array
MATEC Web of Conferences, 2018 The sparse arrays can reduce the cost of beamforming, it greatly reduces the number of actual array elements. However, it also brings about the problem of information loss.
Di Jiaying +3 more
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Random SBT Precoding for Angle Estimation of mmWave Massive MIMO Systems Using Sparse Arrays Spacing
IEEE Access, 2020 In this article, we consider the estimation of angle of arrival (AoA) and angle of departure (AoD) for mmWave MIMO channels. For mmWave systems, there is typically a large number of antennas but limited radio frequency (RF) chains.
Yuan-Pei Lin, Ting-Ming Yang
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Grid-free compressive beamforming [PDF]
, 2015 The direction-of-arrival (DOA) estimation problem involves the localization of a few sources from a limited number of observations on an array of sensors, thus it can be formulated as a sparse signal reconstruction problem and solved efficiently with ...
Gerstoft, Peter, Xenaki, Angeliki
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Azimuth DOA Estimation Using Concentric Coprime Uniform Circular Array With Sparse Bayesian Learning
IEEE AccessEstimation of direction-of-arrival (DOA) is a fundamental problem in array signal processing. The uniform circular array (UCA) is a highly useful array geometry for DOA estimation, especially in electronic warfare (EW), as it possesses useful properties ...
Sanjay Pandav, P. Ubaidulla
doaj +1 more source