Direction-of-arrival estimation for uniform circular arrays under small sample size

Jiang, Guangyao; Mao, Xingpeng; Liu, Yongtan

doi:10.21629/jsee.2016.06.02

Cited by 5 publications

(2 citation statements)

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“…Root-MUSIC has been developed to be applicable for Uniform Circular Arrays (UCAs) so that it can provide 360 • azimuthal coverage [31,32]. The UCA Root-MUSIC transforms the array measurement data from element space to the Beamspace Sample Covariance Matrix (BSCM) using Beamspace Transform (BT), which is based on the phase mode excitation.…”

Section: Introductionmentioning

confidence: 99%

The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy

2019

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Several works show that the linear Angle of Arrival (AoA) methods such as Projection Matrix (PM) have low computational complexity compared to the subspace methods. Although the PM method is classified as a subspace method, it does not need decomposition of the measured matrix. This work investigates the effect of the sampled columns within the covariance matrix on the projection matrix construction. To the authors' knowledge, this investigation has not been addressed in the literature. Unlike the subspace methods such as Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Minimum Norm, Propagator, etc., which have to use a specific number of columns, we demonstrate this aspect is not applicable in the PM method. To this end, the projection matrix is formed based on a various number of sampled columns to estimate the arrival angles. A theoretical analysis is accomplished to illustrate the relationship between the number of the sampled columns and the degrees of freedom (DOFs). The analysis shows that with the same aperture size, the DOFs can be increased by increasing only the number of sampled columns in the projection matrix calculation step. An intensive Monte Carlo simulation for different scenarios is presented to validate the theoretical claims. The estimation accuracy of the PM method, based on the proposed selected sampling methodology outperforms all the other techniques with less complexity compared to the Capon and MUSIC methods. The estimation accuracy is evaluated in terms of Root Mean Square Error (RMSE) and the Probability of Successful Detection (PSD). The results are presented and discussed.

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Section: Introductionmentioning

confidence: 99%

The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy

2019

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“…Exploiting the special geometry of a uniform linear array (ULA), one can also find source DOA by polynomial rooting with search-free computations using the well-known root-MUSIC algorithm [10]. Besides, numerous useful modifications of ESPRIT and root-MUSIC have been proposed with circular and other kinds of arrays [11,12]. As the array structures used in these techniques are still rather specific, many promising attempts such as array interpolation (AI) [13], manifold separation technique (MST) [14], and Fourier-domain (FD) root-MUSIC [15] have been proposed recently to extend ESPRIT and root-MUSIC to more general classes of array configurations.…”

Section: Introductionmentioning

confidence: 99%

Reduced-Complexity Direction of Arrival Estimation Using Real-Valued Computation with Arbitrary Array Configurations

Yan

Jun

Shuai

et al. 2018

International Journal of Antennas and Propagation

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A low-complexity algorithm is presented to dramatically reduce the complexity of the multiple signal classification (MUSIC) algorithm for direction of arrival (DOA) estimation, in which both tasks of eigenvalue decomposition (EVD) and spectral search are implemented with efficient real-valued computations, leading to about 75% complexity reduction as compared to the standard MUSIC. Furthermore, the proposed technique has no dependence on array configurations and is hence suitable for arbitrary array geometries, which shows a significant implementation advantage over most state-of-the-art unitary estimators including unitary MUSIC (U-MUSIC). Numerical simulations over a wide range of scenarios are conducted to show the performance of the new technique, which demonstrates that with a significantly reduced computational complexity, the new approach is able to provide a close accuracy to the standard MUSIC.

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Decoupling self‐correcting method for non‐uniform dual circular array

Zhang¹,

Chen²,

Liu³

2019

J. eng.

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Direction-of-arrival estimation for uniform circular arrays under small sample size

Cited by 5 publications

References 0 publications

The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy

The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy

Reduced-Complexity Direction of Arrival Estimation Using Real-Valued Computation with Arbitrary Array Configurations

Decoupling self‐correcting method for non‐uniform dual circular array

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