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Article

Two Rapid Power Iterative DOA Estimators for UAV Emitter Using Massive/Ultra-Massive Receive Array

by
Yiwen Chen
1,
Qijuan Jie
1,
Yiqiao Zhang
1,
Feng Shu
1,*,
Xichao Zhan
1,
Shihao Yan
2,
Wenlong Cai
3,
Xuehui Wang
1,
Zhongwen Sun
1,
Peng Zhang
1 and
Peng Chen
1
1
School of Information and Communication Engineering, Hainan Unversity, Haikou 570228, China
2
School of Science and Security Research Institute, Edith Cowan University, Perth, WA 6027, Australia
3
National Key Laboratory of Science and Technology on Aerospace Intelligence Control, Beijing Aerospace Automatic Control Institute, Beijing 100854, China
*
Author to whom correspondence should be addressed.
Drones 2023, 7(6), 361; https://doi.org/10.3390/drones7060361
Submission received: 26 April 2023 / Revised: 26 May 2023 / Accepted: 29 May 2023 / Published: 30 May 2023
(This article belongs to the Special Issue UAVs Communications for 6G)
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Abstract

To provide rapid direction finding (DF) for unmanned aerial vehicle (UAV) emitters in future wireless networks, a low-complexity direction of arrival (DOA) estimation architecture for massive multiple-input multiple-output (MIMO) receiver arrays is constructed. In this paper, we propose two strategies to address the extremely high complexity caused by eigenvalue decomposition of the received signal covariance matrix. Firstly, a rapid power iterative rotational invariance (RPI-RI) method is proposed, which adopts the signal subspace generated by power iteration to obtain the final direction estimation through rotational invariance between subarrays. RPI-RI causes a significant complexity reduction at the cost of a substantial performance loss. In order to further reduce the complexity and provide good directional measurement results, the rapid power iterative polynomial rooting (RPI-PR) method is proposed, which utilizes the noise subspace combined with the polynomial solution method to obtain the optimal direction estimation. In addition, the influence of initial vector selection on convergence in the power iteration is analyzed, especially when the initial vector is orthogonal to the incident wave. Simulation results show that the two proposed methods outperform the conventional DOA estimation methods in terms of computational complexity. In particular, the RPI-PR method achieves more than two orders of magnitude lower complexity than conventional methods and achieves performance close to the Cramér–Rao Lower Bound (CRLB). Moreover, it is verified that the initial vector and the relative error have a significant impact on the performance with respect to the computational complexity.
Keywords: UAV; DOA; power iterative; massive MIMO; covariance matrix decomposition; computational complexity UAV; DOA; power iterative; massive MIMO; covariance matrix decomposition; computational complexity

Share and Cite

MDPI and ACS Style

Chen, Y.; Jie, Q.; Zhang, Y.; Shu, F.; Zhan, X.; Yan, S.; Cai, W.; Wang, X.; Sun, Z.; Zhang, P.; et al. Two Rapid Power Iterative DOA Estimators for UAV Emitter Using Massive/Ultra-Massive Receive Array. Drones 2023, 7, 361. https://doi.org/10.3390/drones7060361

AMA Style

Chen Y, Jie Q, Zhang Y, Shu F, Zhan X, Yan S, Cai W, Wang X, Sun Z, Zhang P, et al. Two Rapid Power Iterative DOA Estimators for UAV Emitter Using Massive/Ultra-Massive Receive Array. Drones. 2023; 7(6):361. https://doi.org/10.3390/drones7060361

Chicago/Turabian Style

Chen, Yiwen, Qijuan Jie, Yiqiao Zhang, Feng Shu, Xichao Zhan, Shihao Yan, Wenlong Cai, Xuehui Wang, Zhongwen Sun, Peng Zhang, and et al. 2023. "Two Rapid Power Iterative DOA Estimators for UAV Emitter Using Massive/Ultra-Massive Receive Array" Drones 7, no. 6: 361. https://doi.org/10.3390/drones7060361

APA Style

Chen, Y., Jie, Q., Zhang, Y., Shu, F., Zhan, X., Yan, S., Cai, W., Wang, X., Sun, Z., Zhang, P., & Chen, P. (2023). Two Rapid Power Iterative DOA Estimators for UAV Emitter Using Massive/Ultra-Massive Receive Array. Drones, 7(6), 361. https://doi.org/10.3390/drones7060361

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