Estimating 2-D angles of arrival via two parallel linear arrays

Yin, Qinye; Newcomb, R.W.; Zou, Liyong

doi:10.1109/icassp.1989.267051

Cited by 136 publications

(66 citation statements)

References 9 publications

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“…The elevation (θ) is estimated from the Q matrix and azimuth (φ) from the R matrix. The proposed method has several advantages over the methods in [5][6][7][8][9][10][11][12][13][14][15][16]. First, the proposed method does not require spatial smoothing [3,4] which results in a reduction in the computational complexity and cost.…”

Section: Introductionmentioning

confidence: 93%

“…Fourth, the proposed method utilizes only a single snapshot of the received data to estimate the DOA for incident sources. This significantly reduces the computational load and makes the proposed method a superior candidate for real-time implementation, whereas the methods in [5][6][7][8][9][10][11][12][13][14][15][16] require a large number of snapshots (e.g., 100 to 200) in order to produce a quality estimate. Fifth, computing the QR factorization for the data matrix using Toeplitz structure [17] in the proposed method requires only O((N + 1) 2 ) operations while calculating regular data matrix with dimension (N × N ) using the singular value decomposition (SVD) of the data matrix or the Eigen value decomposition (EVD) of the covariance matrix which have been heavily used by many existing schemes requires O(N 3 ) operations [18].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, several interesting techniques have been developed to resolve the 2D DOA estimation of multiple incoming incident sources [5][6][7][8][9][10][11][12][13][14]. However, most of these techniques are only applicable when the signals are uncorrelated.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Two Uniform Linear Arrays for Non-Coherent and Coherent Sources for Two Dimensional Source Localization

Omer¹,

Tayem²,

Hussain³

2014

PIER Letters

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Abstract-This paper presents a novel method for the two-dimensional direction of arrival (DOA) estimation based on QR decomposition. A configuration with two uniform linear antenna arrays (ULAs) is employed for the joint estimation of elevation (θ) and azimuth (φ) angles. Q data matrix will estimate the azimuth angle while R data matrix will estimate the elevation angle. The proposed method utilizes only a single snapshot of the received data and constructs a Toeplitz data matrix. This reduces the computational complexity of the proposed method to O((N + 1) 2 ) from O(N 3 ) for SVD based methods. The structure of the data matrix also favors the 2D DOA estimation for both coherent and non-coherent source signals. Simulation results are presented, and performance of the proposed method is compared with the Matrix Pencil method for 2D DOA estimation of multiple incident source signals.

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Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Two Uniform Linear Arrays for Non-Coherent and Coherent Sources for Two Dimensional Source Localization

Omer¹,

Tayem²,

Hussain³

2014

PIER Letters

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“…Utilizing the geometry of TP-ULAs, Yin et al [4,5] proposed a DOA matrix algorithm which has a lower computational load than 2-D MUSIC; however, its performance is poor. It needs to be improved when compared to the CRB [6,7].…”

Section: Introductionmentioning

confidence: 99%

Decoupled Unitary Esprit Algorithm for 2-D Doa Estimation

Jiang¹,

Gan²

2012

PIER C

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Abstract-In this paper, a new decoupled Unitary ESPRIT algorithm for two-dimensional (2-D) direction-of-arrival (DOA) estimation is presented. By exploiting the centro-symmetric array configurations of two parallel uniform linear arrays (TP-ULAs) and utilizing the via rotational invariance techniques, the proposed algorithm has advantages as listed below. First, the algorithm enables decoupling the estimation problem into a two-step estimation problem and obtains the automatically matched 2-D DOAs. Second, employing the elements of the array fully, the algorithm can estimate 2-D DOAs up to 2(M − 1), where 2M is the sensor number of the array. Besides, the computational complexity of the proposed algorithm is lower than other representative 2-D DOA estimation methods. Simulation results are presented to show the effectiveness of the proposed method.

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“…Direction of arrival estimation is undoubtedly a key technology in array signal processing. Among the various arrays like the parallel uniform linear array [5], the rectangular array [6], and the circular array [7]. L-shaped array, consisting of two linear subarrays connected orthogonally at one end of each subarray, is a commonly used two-dimensional DOA array.…”

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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Estimating 2-D angles of arrival via two parallel linear arrays

Cited by 136 publications

References 9 publications

Two Uniform Linear Arrays for Non-Coherent and Coherent Sources for Two Dimensional Source Localization

Two Uniform Linear Arrays for Non-Coherent and Coherent Sources for Two Dimensional Source Localization

Decoupled Unitary Esprit Algorithm for 2-D Doa Estimation

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

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