Efficient Augmented ESPRIT-based Direction-of-Arrival Estimation Algorithm for Random Arrays

Song LIU; Yucai PANG

doi:10.11999/JEIT180672

Volume 41 Issue 6

Jun. 2019

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Song LIU, Yucai PANG. Efficient Augmented ESPRIT-based Direction-of-Arrival Estimation Algorithm for Random Arrays[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1324-1329. doi: 10.11999/JEIT180672

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Song LIU, Yucai PANG. Efficient Augmented ESPRIT-based Direction-of-Arrival Estimation Algorithm for Random Arrays[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1324-1329. doi: 10.11999/JEIT180672

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Efficient Augmented ESPRIT-based Direction-of-Arrival Estimation Algorithm for Random Arrays

doi: 10.11999/JEIT180672

Song LIU,
Yucai PANG^,

School of Communication and Information Engineering, Chongqing University of Post and Telecommunications, Chongqing 400065, China

Funds: The Natural Science Foundation of Chongqing Municipal Education Commission (KJ1704079, KJQN201800631)

Received Date: 2018-07-06
Rev Recd Date: 2019-01-15

Available Online: 2019-01-26

Publish Date: 2019-06-01

Abstract

Abstract

As for super resolution Direction-of-Arrival (DoA) estimation with random arrays, it is still challenged to obtain efficient and statistically unbiased estimates. Based on Augmented Estimation of Signal Parameters via Rotational Invariance Techniques (AESPRIT), an efficient DoA estimation algorithm is proposed for random arrays. AESPRIT is modified with a closed loop structure; Array Interpolation Technique (AIT) is utilized to provide the initial phase compensation angles to the loop. Therefore, the final DoA estimates can be calculated efficiently and accurately through iteration. The proposed algorithm gives algebraic solution directly and has low computational complexity. At the same time, the results are statistically unbiased because no manifold mapping or mode truncation error is introduced. Simulations verify the effectiveness of the proposed algorithm.

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References

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