An L-shaped array for estimating 2-D directions of wave arrival

Hua, Yingbo; Sarkar, Tapan K.; Weiner, D.D.

doi:10.1109/8.68174

Cited by 228 publications

(105 citation statements)

References 4 publications

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“…For comparison, the propagator method [6,9] and the ESPRIT method [8,11] with correct pairing are simultaneously executed.…”

Section: Simulation Resultsmentioning

confidence: 99%

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Passive Source Localization of Sensor Arrays

Liang¹,

Liu²

2012

Sensor Array

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“…For comparison, the propagator method [6,9] and the ESPRIT method [8,11] with correct pairing are simultaneously executed.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Let the 0 th sensor be the phase reference point. After sampled with a proper rate that satisfies the Nyquist rate, the signal received by the i th sensor can be expressed as [5][6][7][8][9][10][11] …”

Section: Description Of the Proposed Algorithmmentioning

confidence: 99%

Passive Source Localization of Sensor Arrays

Liang¹,

Liu²

2012

Sensor Array

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“…L-shaped array, consisting of two linear subarrays connected orthogonally at one end of each subarray, is a commonly used two-dimensional DOA array. It features simple structure and relatively high estimation accuracy in practice [8]. Meanwhile in recent years, the two-dimensional DOA estimation as a symbol of array signal processing has become a hot spot.…”

Section: Introductionmentioning

confidence: 99%

Low complexity 2D-DOA estimation algorithm for non-uniform L-shaped array

Yang¹,

Cheng²,

Lv³

et al. 2016

Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

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Abstract. In this paper, we discussed the problem of two-dimensional (2D) direction of arrival (DOA) estimation for non-uniform L-shaped array, and for this, a low complexity multiple signal classification (MUSIC) algorithm is proposed. The proposed algorithm uses two one-dimensional searches to achieve the joint estimation of 2-dimensional DOA so as to avoid the high computational cost within 2D-MUSIC algorithm. And the angle estimation performance is very close to the 2D-MUSIC algorithm. The proposed algorithm achieves a good balance between the estimation accuracy and complexity.

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“…Co mbination of linear arrays is considered in literature and has shown improve-ments in array performance specially the accuracy of DOA estimation algorith ms. So me of these structures are parallel linear arrays and Displaced Sensor Arrays (DSAs), Lshaped and two L-shaped arrays, V-shaped, Y-shaped, Uniform Rectangular Arrays (URA), hexagonal arrays and so on [6][7][8][9][10][11]. Each configuration has particular properties and capabilit ies.…”

Section: Introductionmentioning

confidence: 99%

Improving LMS/NLMS-Based Beamforming Using Shirvani-Akbari Array

Moghaddam¹,

Akbari²

2012

AJSP

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ULA is the most common geometry exp lo ited in array signal processing. In the beamforming operation, employing the ULA leads to obtaining narrower beamwidth with respect to other geometries in similar element numbers. Recently, Shirvani and Akbari proposed a new array by adding two elements to the ULA in top and bottom of the array axis, named as SAA. Th is new array offers a considerable imp rovement in DOA estimation performance in detection and resolution of signal sources placed at angles close to the array endfires. In this article, the performance of the proposed SAA is investigated especially in beamforming and co mpared with ULA. LMS and NLMS algorith ms that are popular adaptive beamforming methods are used for evaluation and co mparing the performance of SAA and ULA. Considering array factor, mean square erro r and bit error rate metrics, simu lation results show improved convergence speed and higher data transmission accuracy in different signal source locations, boresight angles as well as endfire ones, for SAA with respect to ULA.

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An L-shaped array for estimating 2-D directions of wave arrival

Cited by 228 publications

References 4 publications

Passive Source Localization of Sensor Arrays

Passive Source Localization of Sensor Arrays

Low complexity 2D-DOA estimation algorithm for non-uniform L-shaped array

Improving LMS/NLMS-Based Beamforming Using Shirvani-Akbari Array

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