A novel micro-motion feature extraction and estimation method for multicomponent signal

Ruonan Li; Zhiwei Yang; Min Hu; Xianghai Li; Guisheng Liao

doi:10.1117/12.2655340

2 November 2022 A novel micro-motion feature extraction and estimation method for multicomponent signal

Ruonan Li, Zhiwei Yang, Min Hu, Xianghai Li, Guisheng Liao

Proceedings Volume 12455, International Conference on Signal Processing and Communication Security (ICSPCS 2022); 1245502 (2022) https://doi.org/10.1117/12.2655340
Event: International Conference on Signal Processing and Communication Security (ICSPCS 2022), 2022, Dalian, China

Abstract

The fluent ship targets with micro-motion which is caused by oceanic waves leading to defocused images. Due to the large size ship, there is a multi-component echo signal in one range bin, thus it is crucial to extract the micro-Doppler (m-D) features quickly and precisely to refocus the images. This paper puts forward a novel micro-motion feature extraction and estimation method. The method is composed of two steps, and the first step is preprocessing to do the Short-Time Fourier Transform (STFT). After that, we propose a new form of synchrosqueezing transform to concentrate the energy spread curves which can be established as a state translation model. Then in the second step, we use the RFS-based Bernoulli filter to estimate the parameters of the multi-component signal. In this step, the method avoids the disturbance of stray points and empty areas so that the m-D parameters can be estimated accurately. The experimental results prove the availability of the proposed method and the accuracy of the estimation of m-D parameters.

Citation Download Citation

Ruonan Li, Zhiwei Yang, Min Hu, Xianghai Li, and Guisheng Liao "A novel micro-motion feature extraction and estimation method for multicomponent signal", Proc. SPIE 12455, International Conference on Signal Processing and Communication Security (ICSPCS 2022), 1245502 (2 November 2022); https://doi.org/10.1117/12.2655340

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