DOA estimation exploiting distributed array with arbitrary subarray orientations
Zhang, Yimin D. Chowdhury, Md Waqeeb T. S. Ding, Yanwu Shen, Dan Pham, Khanh D. Blasch, Erik Chen, Genshe
Zhang, Yimin D.
Chowdhury, Md Waqeeb T. S.
Ding, Yanwu
Shen, Dan
Pham, Khanh D.
Blasch, Erik
Chen, Genshe
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2024
Type
Conference paper
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Keywords
Cube satellite network,Direction-of-arrival estimation,Distributed array,Group sparsity,Sparse array,Unmanned aerial vehicle
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Citation
Zhang, Y.D., Chowdhury, M.W.T.S., Ding, Y., Shen, D., Pham, K., Blasch, E., Chen, G. DOA estimation exploiting distributed array with arbitrary subarray orientations. (2024). Proceedings of the IEEE Radar Conference. DOI: 10.1109/RadarConf2458775.2024.10548034
Abstract
This paper considers a two-dimensional direction-of-arrival (DOA) estimation problem from a collaborative, distributed antenna array where each subarray is a distributed sensing node that is arbitrarily oriented. While the relative locations of the subarrays are not precisely known, it is assumed that the configuration of each subarray is locally calibrated whereas the cross-covariance matrix between a pair of distributed nodes includes an unknown phase difference. Without explicitly estimating such unknown phase difference, subspace-based DOA estimation methods fail to coherently utilize the subarrays to locate the DOAs of the impinging signals. We propose a group sparsity-based approach to achieve accurate DOA estimation that is resilient to unknown phase disparities between subarrays. Simulation results clearly illustrate the effectiveness of the group sparsity-based approach using group LASSO, and the superiority over subspace-based methods, such as the MUSIC algorithm, is demonstrated. © 2024 IEEE.
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Description
Publisher
Institute of Electrical and Electronics Engineers Inc.
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Series
2024 IEEE Radar Conference, RadarConf 2024. 6 May 2024 through 10 May 2024.
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1097-5764