Author(s)

XinYu Weng

Affiliation(s)

Tianjin University of Technology and Education, Tianjin 300222, China.

Corresponding Author

XinYu Weng

ABSTRACT

To tackle the problems of high computational complexity and cumbersome engineering deployment posed by traditional subspace-based direction-of-arrival (DOA) estimation algorithms, this study presents a low-complexity DOA estimation approach designed specifically for uniform linear arrays (ULA). The key innovation of the proposed method is the elimination of eigenvalue decomposition or singular value decomposition (EVD/SVD)—two core components of classical subspace-based techniques. Instead, it employs a strategy of array segmentation and matrix reconstruction. In detail, the ULA is first split into two separate subarrays, and their cross-covariance matrix is used to build a joint cross-covariance matrix. An equivalent signal subspace is then directly generated via a linear transformation, which greatly simplifies the computational procedure. Finally, by exploiting the rotation invariance principle of ESPRIT, the proposed approach realizes fast and precise DOA estimation. Theoretical analyses and simulation results indicate that, in comparison with traditional subspace-based algorithms, the proposed method reduces computational complexity significantly while retaining comparable estimation accuracy, thus improving the overall efficiency of DOA estimation.

KEYWORDS

DOA estimation; Joint cross-covariance matrix; Signal subspace; ESPRIT algorithm

CITE THIS PAPER

XinYu Weng. Optimization of ESPRIT algorithm and fast DOA estimation for uniform linear arrays. Journal of Computer Science and Electrical Engineering. 2026, 8(2): 12-18. DOI: https://doi.org/10.61784/jcsee3122.

REFERENCES

[1] Liu Wei, Haardt Martin, Greco Maria S, et al. Twenty-Five Years of Sensor Array and Multichannel Signal Processing: A review of progress to date and potential research directions. IEEE Signal Processing Magazine, 2023, 40(4): 80-91.

[2] Chen Hua, Lin Hongguang, Liu Wei, et al. Augmented Multi-Subarray Dilated Nested Array With Enhanced Degrees of Freedom and Reduced Mutual Coupling. IEEE Transactions on Signal Processing, 2024, 72: 1387-1399.

[3] Xu Zhengguang, Chen Yaling, Zhang Peng. A Sparse Uniform Linear Array DOA Estimation Algorithm for FMCW Radar. IEEE Signal Processing Letters, 2023, 30: 823-827.

[4] Li Ping, Li Jianfeng, Zhao Gaofeng. Low complexity DOA estimation for massive UCA with single snapshot. Journal of Systems Engineering and Electronics, 2022, 33(1): 22-27.

[5] Tian Quan, Cai Ruiyan. A Low-Complexity DOA Estimation Algorithm for Distributed Source Localization. IEEE Transactions on Instrumentation and Measurement, 2023, 72: 1-4.

[6] Schmidt R. Multiple emitter location and signal parameter estimation. IEEE Transactions on Antennas and Propagation, 1986, 34(3): 276-280.

[7] Yang Zai. Nonasymptotic Performance Analysis of ESPRIT and Spatial-Smoothing ESPRIT. IEEE Transactions on Information Theory, 2023, 69(1): 666-681.

[8] Hussain Ahmed A, Tayem Nizar, Soliman Abdel-Hamid. Low Complexity DOA Estimation of Multiple Coherent Sources Using a Single Direct Data Snapshot. IEEE Access, 2024, 12: 2371-2388.

[9] Ren QS, Willis AJ. Fast root MUSIC algorithm. Electronics letters, 1997, 33(6): 450-451.

[10] Veerendra D, Niranjan K R, Malik Iram, et al. Modified Root-MUSIC Algorithm for Target Localization Using Nystrom Approximation. IEEE Sensors Journal, 2024, 24(8): 13209-13216.

[11] Qian Yang, Han Xiaolei, Shi Xinlei, et al. Direct position determination of non-Gaussian sources for sensor arrays via improved rooting subspace data fusion method. IEEE Sensors Journal, 2023, 23(20): 25307-25315.

[12] Liu Aihua, Zhang Xin, Yang Qiang, et al. Combined root-MUSIC algorithms for multi-carrier MIMO radar with sparse uniform linear arrays. IET Radar, Sonar & Navigation, 2019, 13(1): 89-97.

[13] Yeh Chien-Chung. Simple computation of projection matrix for bearing estimations. IEE Proceedings F (Communications, Radar and Signal Processing), 1987, 134(2): 146-150.

[14] Marcos S, Marsal A, Benidir M. Performances analysis of the propagator method for source bearing estimation. Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing, 1994, 4: 237-240.

[15] Bressner T A H, Johannsen U, Smolders A B. Single shot DoA estimation for large-array base station systems in multi-user environments. Loughborough Antennas & Propagation Conference (LAPC 2017), Loughborough, UK, 2017: 1-4.

[16] Tian Xiyan, Lei Jinhui, Du Liufeng. A Generalized 2-D DOA Estimation Method Based on Low-Rank Matrix Reconstruction. IEEE Access, 2018, 6: 17407-17414.

[17] Xi Nie, Li Liping. A Computationally Efficient Subspace Algorithm for 2-D DOA Estimation with L-shaped Array. IEEE Signal Processing Letters, 2014, 21(8): 971-974. DOI: 10.1109/LSP.2014.2321791

[18] Yan Fenggang, Rong Jiajia, Liu Shuai, et al. Joint cross-covariance matrix based fast direction of arrival estimation. Systems Engineering and Electronics, 2018, 40(4): 733-738.

[19] Lawal Teslim, Ofuzim Onyero Walter. Total Least Squares Implementation of ESPRIT Algorithm for Signal Processing. 2024.

[20] Chen Chen, Zhang Zhengyi, Lian Haisheng. A Low-Complexity Joint Angle Estimation Algorithm for Weather Radar Echo Signals Based on Modified ESPRIT. Journal of Industrial Engineering and Applied Science, 2025, 3(2): 33-43.