Two-Dimensional DOA Estimation Algorithm for Coherent Signal Sources Based on Matrix Reconstruction
Authors: 
Huijing Dou, Fan Yang, Ziheng XiaoAuthors Info & Claims
Abstract
In the process of array signal processing, due to the influence of multi-path propagation and other factors, there will be a large number of coherent signal sources. The performance of the traditional two-dimensional direction of arrival (2D DOA) estimation algorithm will decline sharply or even fail under the background of coherent sources. To address this problem, an improved 2D DOA algorithm based on matrix reconstruction is proposed in this paper. Since the presence of a coherent signal source can lead to the rank loss of the received data covariance matrix of the antenna, this proposed method constructs the Toeplitz matrix solves this problem, based on this, through the conjugate rearrangement of the data, the original data is fully utilized to obtain more accurate estimation results. Finally, simulation results show that this method effectively solves the problem of coherent signal sources.
References
[1]
Zhang X F, Li J F, Xu D Z. Sensor array source location [M]. Beijing: Publishing House of Electronics Industry, 2019.
[2]
Schmidt R. Multiple emitter location and signal parameter estimation[J].IEEE Trans. Antennas and Propagation, 1986, 34 (3): 276--280.
[3]
Roy R, Kailath T. ESPRIT-estimation of signal parameters via rotational invariance techniques[J]. IEEE Trans. Acoustics, Speech and Signal Processing, 1989, 37 (7): 984--995.
[4]
Qing W, Hang Y, Hua C, et al. A Low-Complexity Method for Two-Dimensional Direction-of-Arrival Estimation Using an L-Shaped Array[J]. Sensors, 2017, 17(1):190.
[5]
DOU H J, ZHU Z Y, GAO L J. Two-dimensional MUSIC Spectral Peak Search Algorithm Based on Chicken Swarm Optimization. Journal of Beijing University of Technology, 2018, 44(11):1409--1413.
[6]
Wax M, Sheinvald J. Direction finding of coherent signals via spatial smoothing for uniform circular arrays[J]. IEEE Transactions on Antennas & Propagation, 2002, 42(5):613--620.
[7]
Du W, Kirlin R L. Improved spatial smoothing techniques for DOA estimation of coherent signals[J]. Signal Processing IEEE Transactions on, 1991, 39(5): 1208--1210.
[8]
Thompson J S, Grant P M, Mulgrew B. Generalised algorithm for DOA estimation in a passive sonar[J]. IEE Proceedings F-Radar and Signal Processing, 2002, 140(5): 339--340.
[9]
Gu Z, Gunawan E. A performance analysis of multipath direction finding with temporal smoothing [J]. IEEE Signal Processing Letters, 2003, 10(7):200--203.
[10]
Jun, Li, Qiu-Hua. DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing.[J]. Sensors (Basel, Switzerland), 2018, 18(3):902--910.
[11]
Shi Y, Mao X, Qian C, et al. Robust Relaxation for Coherent DOA Estimation in Impulsive Noise[J]. IEEE Signal Processing Letters, 2019:410--414.
[12]
Shahimaeen A, Dehghani M J. Two-dimensional DOA estimation for coherent signals using a novel covariance-like matrix[J]. Transactions on Emerging Telecommunications Technologies, 2019, 30(6): 180--195.
Index Terms
- Two-Dimensional DOA Estimation Algorithm for Coherent Signal Sources Based on Matrix Reconstruction
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Published In
October 2020
552 pages
ISBN:9781450387835
DOI:10.1145/3436369
Copyright © 2020 ACM.
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- Beijing University of Technology
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 11 January 2021
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- Research-article
- Research
- Refereed limited
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- National Natural Science Foundation of China
- Beijing Education Commission Research and Development Program Funding Project
Conference
ICCPR 2020
ICCPR 2020: 2020 9th International Conference on Computing and Pattern Recognition
October 30 - November 1, 2020
Xiamen, China
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