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Dictionary Adaptive DOA Estimation Algorithm Based on Compressed Sensing

Published: 28 February 2024 Publication History

Abstract

Because traditional subspace DOA estimation algorithms still have poor estimation performance and even algorithm failure under the conditions of few snapshots, low signal-to-noise ratio (SNR) and source coherence, this paper studies the DOA estimation algorithm based on compressed sensing theory. Based on the sparse reconstruction conditions, this paper analyzes the current existing equal angle and equal sine grid division methods on the performance of the array flow matrix, and proposes a DOA estimation algorithm based on an adaptive dictionary. According to the interval range of the target angle, a better division scheme is selected to improve the DOA estimation accuracy. At the same time, the atoms in the dictionary that are not related to the target angle are deleted to reduce the dictionary dimension, thereby reducing the amount of calculation.

References

[1]
E. J. Candès. 2008. The Restricted Isometry Property and its Implications for Compressed Sensing. Comptes Rendus Mathematique 346, 9 (2008), 589–592.
[2]
D. L. Donoho. 2006. Compressed Sensing. IEEE Transactions on Information Theory 52, 4 (2006), 1289–1306.
[3]
D. L. Donoho and X. Huo. 2001. Uncertainty Principles and Ideal Atomic Decomposition. IEEE Transactions on Information Theory 47, 7 (2001), 2845–2862.
[4]
T. Jia, H. Wang, and X. Shen. 2020. A study of compressed sensing single-snapshot DOA estimation based on the RIPless theory. Telecommunication Systems: Modelling, Analysis, Design and Management 74, 4 (2020), 531–537.
[5]
X. Li, X. Ma, and S. et al. Yan. 2013. Single snapshot DOA estimation by compressive sampling. Applied Acoustics 74, 7 (2013), 926–930.
[6]
Z. G. Li, S. Q. Li, and S. L. Wen. 2017. An improved DOA estimation method for orthogonal matching tracking. Measurement and Control Technology 36, 01 (2017), 27–31+36.
[7]
X. M. Luan and J. B. Gong. 2016. DOA estimation algorithm based on sparse representation of equal sine interval. Information Technology01 (2016), 177–179.
[8]
Xuejun Mao and Hanhuai Pan. 2013. An Improved DOA Estimation Algorithm Based on Wavelet Operator. Journal of Communications 8, 12 (2013), 839–844.
[9]
J. Y. Tang, F. Cao, and L. Q. Xue. 2018. SARMP compressed sensing DOA estimation algorithm applied to anti-radiation missiles. Tactical missile technology06 (2018), 106–112.
[10]
Q. Yang. 2019. Research on DOA estimation algorithm based on compressed sensing. Ph. D. Dissertation. Xidian University.
[11]
J. Yin and T. Chen. 2011. Direction of Arrival Estimation Using a Sparse Representation of Array Covariance Vectors. IEEE Transactions on Signal Processing 59, 9 (2011), 4489–4493.
[12]
Li Zhang, Ding Wang, and Ying Wu. 2014. Performance Analysis of TDOA and FDOA Location by Differential Calibration with Calibration Sources. Journal of Communications 9, 6 (2014), 483–489.

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        ICCPR '23: Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition
        October 2023
        589 pages
        ISBN:9798400707988
        DOI:10.1145/3633637
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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        Association for Computing Machinery

        New York, NY, United States

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        Published: 28 February 2024

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        Author Tags

        1. DOA estimation
        2. adaptive dictionary
        3. compressed sensing
        4. spatial division

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