2019
DOI: 10.18280/ts.360608
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Compressive Sensing Based Two-Dimensional DOA Estimation Using L-Shaped Array in a Hostile Environment

Abstract: In this paper, two-dimensional (2-D) direction of arrival (DOA) estimation problem with an L-shaped array is investigated. One of the major areas of concern of modern urban combat is to locate lives trapped in a building in the presence of enemy jamming conditions at very low signal-to-noise ratio. This study provides a suitable design of a tracking system that enables location of trapped survivors in hostile situation. A compressive sensing (CS) based model is proposed for an L-shaped array which offers more … Show more

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Cited by 8 publications
(2 citation statements)
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“…Consider an uniform linear array (ULA) of M sensors with an array manifold matrix of 𝐴(πœƒ) = [π‘Ž(πœƒ 1 ), π‘Ž(πœƒ 2 ) … π‘Ž(πœƒ 𝐾 )], by assuming K number of far-field signals impinging on the ULA. Each column vector of A(ΞΈ) contains the time-delay information of the Kth signal received at the ULA by taking first sensor in the ULA as the [25]. The general representation of the array manifold matrix is as shown below:…”
Section: Doa Estimation By Interpolated Ar (1) Based Sparse Bayesian ...mentioning
confidence: 99%
“…Consider an uniform linear array (ULA) of M sensors with an array manifold matrix of 𝐴(πœƒ) = [π‘Ž(πœƒ 1 ), π‘Ž(πœƒ 2 ) … π‘Ž(πœƒ 𝐾 )], by assuming K number of far-field signals impinging on the ULA. Each column vector of A(ΞΈ) contains the time-delay information of the Kth signal received at the ULA by taking first sensor in the ULA as the [25]. The general representation of the array manifold matrix is as shown below:…”
Section: Doa Estimation By Interpolated Ar (1) Based Sparse Bayesian ...mentioning
confidence: 99%
“…Compressive sensing (CS) [1,2] is a novel paradigm that recovers signals that are sparse in a certain domain, from a small set of compressed measurements. This paradigm has been widely applied in various signal processing applications [3][4][5][6][7][8], ranging from image [9,10], audio [11][12][13], to video [14][15][16][17][18][19].…”
Section: Introductionmentioning
confidence: 99%