An Improved DOA Estimation Approach Using Coarray Interpolation and Matrix Denoising
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College of Information and Communication Engineering, Harbin Engineering University, No. 145 Nantong Street, Harbin 150001, China
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College of Automation, Harbin Engineering University, No. 145 Nantong Street, Harbin 150001, China
3
Depaprtment of Electrical and Computer Engineering, Temple University, Philadelphia, PA 19122, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Zhiguo Shi, Yujie Gu and Rongxing Lu
Sensors 2017, 17(5), 1140; https://doi.org/10.3390/s17051140
Received: 29 March 2017
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Revised: 4 May 2017
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Accepted: 12 May 2017
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Published: 16 May 2017
(This article belongs to the Special Issue Recent Advances in Array Signal Processing and Its Applications in IoT Security)
Co-prime arrays can estimate the directions of arrival (DOAs) of sources with sensors, and are convenient to analyze due to their closed-form expression for the locations of virtual lags. However, the number of degrees of freedom is limited due to the existence of holes in difference coarrays if subspace-based algorithms such as the spatial smoothing multiple signal classification (MUSIC) algorithm are utilized. To address this issue, techniques such as positive definite Toeplitz completion and array interpolation have been proposed in the literature. Another factor that compromises the accuracy of DOA estimation is the limitation of the number of snapshots. Coarray-based processing is particularly sensitive to the discrepancy between the sample covariance matrix and the ideal covariance matrix due to the finite number of snapshots. In this paper, coarray interpolation based on matrix completion (MC) followed by a denoising operation is proposed to detect more sources with a higher accuracy. The effectiveness of the proposed method is based on the capability of MC to fill in holes in the virtual sensors and that of MC denoising operation to reduce the perturbation in the sample covariance matrix. The results of numerical simulations verify the superiority of the proposed approach.
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Keywords:
array interpolation; direction-of-arrival estimation; matrix denoising; MUSIC; nuclear norm minimization
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MDPI and ACS Style
Guo, M.; Chen, T.; Wang, B. An Improved DOA Estimation Approach Using Coarray Interpolation and Matrix Denoising. Sensors 2017, 17, 1140. https://doi.org/10.3390/s17051140
AMA Style
Guo M, Chen T, Wang B. An Improved DOA Estimation Approach Using Coarray Interpolation and Matrix Denoising. Sensors. 2017; 17(5):1140. https://doi.org/10.3390/s17051140
Chicago/Turabian StyleGuo, Muran, Tao Chen, and Ben Wang. 2017. "An Improved DOA Estimation Approach Using Coarray Interpolation and Matrix Denoising" Sensors 17, no. 5: 1140. https://doi.org/10.3390/s17051140
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