Underdetermined DOA estimation of wideband nonstationary signals with completely overlapped TFDs

Jiahui Bing; Yougen Xu; Yi Liang

doi:10.1117/12.3054387

3 January 2025 Underdetermined DOA estimation of wideband nonstationary signals with completely overlapped TFDs

Jiahui Bing, Yougen Xu, Yi Liang

Author Affiliations +

Proceedings Volume 13442, Fifth International Conference on Signal Processing and Computer Science (SPCS 2024); 1344217 (2025) https://doi.org/10.1117/12.3054387
Event: Fifth International Conference on Signal Processing and Computer Science (SPCS 2024), 2024, Kaifeng, China

Abstract

An underdetermined direction-of-arrival (DOA) estimation method is proposed for wideband non-stationary signals with completely overlapped time-frequency distributions (TFDs). In this case, signals cannot be separated based solely on their time-frequency characteristics because of a rank-deficient spatial time-frequency distribution (STFD) matrix. The proposed method uses a moving array to recover the rank of the STFD matrix. Meantime, it vectorizes the matrix to construct a differential virtual co-array, and employs matrix rank minimization to fill the holes of virtual array, thereby enhancing the array processing degree of freedom. This method enables underdetermined DOA estimation of wideband non-stationary signals with completely overlapped TFDs, without suffering from aperture loss or requiring arrays with spatial translation invariant structures. Simulation results demonstrate the effectiveness of the proposed method.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiahui Bing, Yougen Xu, and Yi Liang "Underdetermined DOA estimation of wideband nonstationary signals with completely overlapped TFDs", Proc. SPIE 13442, Fifth International Conference on Signal Processing and Computer Science (SPCS 2024), 1344217 (3 January 2025); https://doi.org/10.1117/12.3054387

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KEYWORDS

Matrices

Detector arrays

Sensors

Time-frequency analysis

Covariance matrices

Interpolation

Signal to noise ratio

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