Abstract
Coprime array offers a larger array aperture than uniform linear array with the same number of physical sensors, and has a better spatial resolution with increased degrees of freedom. However, when it comes to the problem of adaptive beamforming, the existing adaptive beamforming algorithms designed for the general array cannot take full advantage of coprime feature offered by the coprime array. In this paper, we propose a novel coprime array adaptive beamforming algorithm, where both robustness and efficiency are well balanced. Specifically, we first decompose the coprime array into a pair of sparse uniform linear subarrays and process their received signals separately. According to the property of coprime integers, the direction-of-arrival (DOA) can be uniquely estimated for each source by matching the super-resolution spatial spectra of the pair of sparse uniform linear subarrays. Further, a joint covariance matrix optimization problem is formulated to estimate the power of each source. The estimated DOAs and their corresponding power are utilized to reconstruct the interference-plus-noise covariance matrix and estimate the signal steering vector. Theoretical analyses are presented in terms of robustness and efficiency, and simulation results demonstrate the effectiveness of the proposed coprime array adaptive beamforming algorithm.
Original language | English |
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Pages (from-to) | 1099-1112 |
Number of pages | 14 |
Journal | IEEE Transactions on Vehicular Technology |
Volume | 67 |
Issue number | 2 |
DOIs | |
State | Published - Feb 2018 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 1967-2012 IEEE.
Funding
Manuscript received January 16, 2017; revised March 19, 2017; accepted April 23, 2017. Date of publication May 16, 2017; date of current version February 12, 2018. This work was supported in part by Zhejiang Provincial Natural Science Foundation of China under Grant LR16F010002, in part by the National Natural Science Foundation of China under Grant U1401253, and in part by the Fundamental Research Funds for the Central Universities under Grant 2017QNA5009. This paper was presented in part at the IEEE International Conference on Acoustics, Speech and Signal Processing, Shanghai, China, March 2016. The review of this paper was coordinated by Prof. C. Yuen. (Corresponding author: Zhiguo Shi.) C. Zhou and Z. Shi are with the College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China (e-mail: [email protected]; [email protected]).
Funders | Funder number |
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National Natural Science Foundation of China | U1401253 |
Natural Science Foundation of Zhejiang Province | LR16F010002 |
Fundamental Research Funds for the Central Universities | 2017QNA5009 |
Keywords
- Adaptive beamforming
- DOA estimation
- coprime array
- joint covariance matrix optimization
- reconstruction