Computationally efficient 2-D DOA estimation for uniform rectangular arrays

Zhang, Wei; Liu, Wei; Wang, Ju; Wu, Siliang

doi:10.1007/s11045-013-0267-y

Cited by 28 publications

(20 citation statements)

References 15 publications

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“…Recently, the 2D DOA estimation with uniform rectangular arrays (URAs) has attracted widespread concern [2,3,4,5]. Various algorithms have been developed for improving the estimation performance, such as the multiple signal classification (MUSIC) [6], estimation of signal parameters via rotational invariance techniques (ESPRIT) [7] and the matrix pencil (MP) method [8].…”

Section: Introductionmentioning

confidence: 99%

“…The advantages of the proposed method can be given as follows: The methods in [3,4,15,16,17,21] involve the 2D EVD or 2D peak search, while the proposed method can estimate the parameters with 1D subspace-based estimation techniques.The method in [22] can only use the auto-correlations of different subarrays, while the proposed method can use more information including auto-correlations and cross-correlations.The spatial differencing techniques in [18,19] perform a difference operation on the whole subarrays, while the proposed method is only for the auto-correlations and the cross-correlations are kept completely. Thus, the SDMS method has little data loss.…”

Section: Introductionmentioning

confidence: 99%

“…The methods in [3,4,15,16,17,21] involve the 2D EVD or 2D peak search, while the proposed method can estimate the parameters with 1D subspace-based estimation techniques.…”

Section: Introductionmentioning

confidence: 99%

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Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle

Shi

Zhang

et al. 2017

Sensors

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In this paper, we propose a computationally efficient spatial differencing matrix set (SDMS) method for two-dimensional direction of arrival (2D DOA) estimation with uniform rectangular arrays (URAs) in a low-grazing angle (LGA) condition. By rearranging the auto-correlation and cross-correlation matrices in turn among different subarrays, the SDMS method can estimate the two parameters independently with one-dimensional (1D) subspace-based estimation techniques, where we only perform difference for auto-correlation matrices and the cross-correlation matrices are kept completely. Then, the pair-matching of two parameters is achieved by extracting the diagonal elements of URA. Thus, the proposed method can decrease the computational complexity, suppress the effect of additive noise and also have little information loss. Simulation results show that, in LGA, compared to other methods, the proposed methods can achieve performance improvement in the white or colored noise conditions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle

Shi

Zhang

et al. 2017

Sensors

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“…[1,2,3,4,5], which is an important research branch in array signal processing. Many 2D-DOA estimation algorithms have sprung up in recent years in order to improve the performance of angle estimation, which include the two dimensional multiple signal classification(2D MUSIC) algorithm [6], the 2D Unitary estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm [7], the modified 2D-ESPRIT algorithm [8], the matrix pencil method [9], the maximum likelihood method [10,11], the parallel factor (PARAFAC) algorithm [12], and so on [13,14,15,16,17,18,19,20]. However, those 2D-DOA estimation algorithms are confronted with the problem of the high computational complexity generally and they are very difficult to apply in engineering practice.…”

Section: Introductionmentioning

confidence: 99%

Fast Noncircular 2D-DOA Estimation for Rectangular Planar Array

Wen

2017

Sensors

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A novel scheme is proposed for direction finding with uniform rectangular planar array. First, the characteristics of noncircular signals and Euler’s formula are exploited to construct a new real-valued rectangular array data. Then, the rotational invariance relations for real-valued signal space are depicted in a new way. Finally the real-valued propagator method is utilized to estimate the pairing two-dimensional direction of arrival (2D-DOA). The proposed algorithm provides better angle estimation performance and can discern more sources than the 2D propagator method. At the same time, it has very close angle estimation performance to the noncircular propagator method (NC-PM) with reduced computational complexity.

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“…while the subspace-based algorithm in [10] requires neither constructing the correlation matrix of the received data nor performing singular value decomposition (SVD) of the correlation matrix and utilizes the conjugate symmetry property to enlarge the effective array aperture. Another computationally efficient algorithm for URA was proposed in [11], where the complex-valued covariance matrix and the complex-valued search vector are transformed into real-valued ones, and the 2-D problem is decoupled into two 1-D problems with real-valued computations.…”

Section: Introductionmentioning

confidence: 99%

Direction finding and mutual coupling estimation for uniform rectangular arrays

Hou

Chen

et al. 2015

Signal Processing

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A novel two-dimensional (2-D) direct-of-arrival (DOA) and mutual coupling coefficients estimation algorithm for uniform rectangular arrays (URAs) is proposed. A general mutual coupling model is first built based on banded symmetric Toeplitz matrices, and then it is proved that the steering vector of a URA in the presence of mutual coupling has a similar form to that of a uniform linear array (ULA). The 2-D DOA estimation problem can be solved using the rank-reduction method. With the obtained DOA information, we can further estimate the mutual coupling coefficients. A better performance is achieved by our proposed algorithm than those auxiliary sensor-based ones, as verified by simulation results.

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Computationally efficient 2-D DOA estimation for uniform rectangular arrays

Cited by 28 publications

References 15 publications

Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle

Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle

Fast Noncircular 2D-DOA Estimation for Rectangular Planar Array

Direction finding and mutual coupling estimation for uniform rectangular arrays

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