Underdetermined DOA estimation of quasi-stationary signals via Khatri-Rao structure for uniform circular array

Ming Yang Cao; Lei Huang; Cheng Qian; Jia Yin Xue; H. C. So

doi:10.1016/j.sigpro.2014.06.012

Underdetermined DOA estimation of quasi-stationary signals via Khatri-Rao structure for uniform circular array

Ming Yang Cao, Lei Huang, Cheng Qian, Jia Yin Xue, H. C. So

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Abstract

Underdetermined direction-of-arrival (DOA) estimation for quasi-stationary signals impinging on a uniform circular array (UCA) with M sensors is addressed in this paper. We apply the Khatri-Rao (KR) approach to the UCA and obtain a new signal model which is capable of providing O(M²) sensors. Meanwhile, the virtual steering matrix can be decomposed into a product of characteristic matrix depending on the array structure and a Vandermonde matrix bearing the DOA information. The exact number of virtual sensors that the KR-UCA model is able to provide is studied as well. Simulation results are included to demonstrate the effectiveness of the proposed method.

Original language	English (US)
Pages (from-to)	41-48
Number of pages	8
Journal	Signal Processing
Volume	106
DOIs	https://doi.org/10.1016/j.sigpro.2014.06.012
State	Published - Jan 2015
Externally published	Yes

Keywords

Khatri-Rao subspace approach
Manifold separation technique
Quasi-stationary signal
Underdetermined estimation
Uniform circular array

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title = "Underdetermined DOA estimation of quasi-stationary signals via Khatri-Rao structure for uniform circular array",

abstract = "Underdetermined direction-of-arrival (DOA) estimation for quasi-stationary signals impinging on a uniform circular array (UCA) with M sensors is addressed in this paper. We apply the Khatri-Rao (KR) approach to the UCA and obtain a new signal model which is capable of providing O(M2) sensors. Meanwhile, the virtual steering matrix can be decomposed into a product of characteristic matrix depending on the array structure and a Vandermonde matrix bearing the DOA information. The exact number of virtual sensors that the KR-UCA model is able to provide is studied as well. Simulation results are included to demonstrate the effectiveness of the proposed method.",

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AU - Cao, Ming Yang

AU - Huang, Lei

AU - Qian, Cheng

AU - Xue, Jia Yin

AU - So, H. C.

PY - 2015/1

Y1 - 2015/1

N2 - Underdetermined direction-of-arrival (DOA) estimation for quasi-stationary signals impinging on a uniform circular array (UCA) with M sensors is addressed in this paper. We apply the Khatri-Rao (KR) approach to the UCA and obtain a new signal model which is capable of providing O(M2) sensors. Meanwhile, the virtual steering matrix can be decomposed into a product of characteristic matrix depending on the array structure and a Vandermonde matrix bearing the DOA information. The exact number of virtual sensors that the KR-UCA model is able to provide is studied as well. Simulation results are included to demonstrate the effectiveness of the proposed method.

AB - Underdetermined direction-of-arrival (DOA) estimation for quasi-stationary signals impinging on a uniform circular array (UCA) with M sensors is addressed in this paper. We apply the Khatri-Rao (KR) approach to the UCA and obtain a new signal model which is capable of providing O(M2) sensors. Meanwhile, the virtual steering matrix can be decomposed into a product of characteristic matrix depending on the array structure and a Vandermonde matrix bearing the DOA information. The exact number of virtual sensors that the KR-UCA model is able to provide is studied as well. Simulation results are included to demonstrate the effectiveness of the proposed method.

KW - Khatri-Rao subspace approach

KW - Manifold separation technique

KW - Quasi-stationary signal

KW - Underdetermined estimation

KW - Uniform circular array

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JO - Signal Processing

JF - Signal Processing

ER -

Underdetermined DOA estimation of quasi-stationary signals via Khatri-Rao structure for uniform circular array

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