DOA Estimation for Coherent and Incoherent Sources Based on Co-prime Array

Jia, Yong; Li, Zehua; Yan, Chao; Zhong, Xiaoling; Guo, Yong; Yin, Shiying

doi:10.1007/978-3-030-19156-6_57

Cited by 1 publication

(3 citation statements)

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“…Hence, some researchers concentrated on the design of the geometry of the array, attempting to increase the DOF of the array. Co-prime linear array (CLA) is one of the promising techniques therein [13][14][15][16][17][18][19]. A CLA, first proposed in [13] by Pal et al, consists of two ULAs acting as two subarrays with the number of sensors co-prime to each other.…”

Section: Related Workmentioning

confidence: 99%

“…In [15], two operations with which the CLA can be generalized are proposed. Jia et al introduced a DOA estimation algorithm for coherent and incoherent sources based on co-prime array in [16], and Dong et al came up with a method to estimate DOA in the presence of impulsive noise [17]. Furthermore, a proximal gradient-based approach is introduced in [18] to improve the resolution, while Ashok et al proposed in [19] a low-complexity DOA estimation method on the basis of unfolded CLAs.…”

Section: Related Workmentioning

confidence: 99%

“…By far, much research has been conducted to solve the DOA estimation problem [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19], among which the modified multiple signal classification (MUSIC) algorithm based on co-prime linear array (CLA) [10][11][12][13][14][15][16][17][18][19] is considered a high-performance technique. A CLA is composed of two uniform linear arrays (ULAs) as subarrays, and provides a much larger degree of freedom (DOF) than ULAs with the same number of physical sensors, which means that CLA is capable of sensing the incident signals more accurately.…”

Section: Introductionmentioning

confidence: 99%

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DOA Estimation Algorithm for Reconfigurable Intelligent Surface Co-Prime Linear Array Based on Multiple Signal Classification Approach

et al. 2022

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Co-prime linear arrays (CLAs) provide an additional degree of freedom (DOF) with a limited number of physical sensors, and thus help to improve the resolution of direction of arrival (DOA) estimation algorithms. However, the DOF of traditional CLA is restrained by the structure of the array, which cannot be adjusted after deployment. In this paper, we propose a DOA estimation algorithm for reconfigurable intelligent surface co-prime linear array (RIS CLA) based on the multiple signal classification approach. Specifically, an RIS CLA is first constructed on the ground of RIS antenna, by turning on/off specific elements at different times. Then, the covariance matrix of the received signal is vectorized, so as to construct a virtual difference array, whose aperture is considerably expanded. Finally, a spectral peak search on the noise subspace of the received signal of the difference array is conducted to obtain the DOA estimation result. Simulations verify the improvement of the proposed algorithm in terms of DOF and resolution. To be specific, the DOF provided by RIS CLA outnumbers that of CLA by more than 30%, and the resolution of the proposed DOA estimation algorithm is effectively improved, with its accuracy increased up to 70% under the low signal-noise-ratio (SNR) scenario, compared with existing algorithms.

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