Time-frequency preprocessing method of radiation source signal based on cyclic statistics

Dingkun Huang; Xiaopeng Yan; Minghui Lv

doi:10.1117/12.2681035

8 June 2023 Time-frequency preprocessing method of radiation source signal based on cyclic statistics

Dingkun Huang, Xiaopeng Yan, Minghui Lv

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 127073W (2023) https://doi.org/10.1117/12.2681035
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

To improve the real-time performance of radiation source signal time-frequency analysis, a fast radiation source signal time-frequency feature extraction method based on low-order cyclic statistics and Choi-Williams transform is proposed. First, the low-order cyclic statistics of the radiation source signal are calculated. Second, the IFFT is used to recover the cyclic domain signal, and the number of sampling points of the radiation source signal is adaptively controlled by the cyclic mean and IFFT point number. Finally, the recovered signal is used for CWD time-frequency analysis. In order to highlight the time-frequency image features, the geometric features of the signal modulation type are extracted using binary image transformation. Simulation analysis shows that the proposed time-frequency preprocessing method can significantly reduce the computational complexity while maintaining the accuracy of time-frequency features and improving real-time performance, providing effective support for subsequent sorting and recognition and parameter estimation work.

Citation Download Citation

Dingkun Huang, Xiaopeng Yan, and Minghui Lv "Time-frequency preprocessing method of radiation source signal based on cyclic statistics", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 127073W (8 June 2023); https://doi.org/10.1117/12.2681035

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