Abstract
With the rapid growth of the number of UAV, the research of UAV detection and target recognition is a hot spot at present. When detecting UAVs, in addition to the movement of the UAV’s body, the micro-Doppler features of the rotor blades of the UAV are the unique characteristics of detecting UAV. Through the extracted micro-Doppler features, the rotor speed and blade length of the UAV can be calculated, which can be used to recognize the UAV. In this work, the echo models of multiple UAVs are established. In order to extract the micro-Doppler features, the synchrosqueezed transform is used to do time-frequency analysis. There are many components in the micro-Doppler features of multi-UAV. In order to recognize the parameter of each UAV, a ridge path extraction method based on synchrosqueezed transformation is used to separate the components in time-frequency domain. Experimental results show that the proposed method achieves high accuracy in extracting component micro-Doppler features and recognizing UAV information.
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This work was supported by the National Natural Science Foundation of China (61731006), and was partly supported by the 111 Project No. B17008.
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Li, S., Si, X., Zhang, C., Liang, J. (2023). Micro-doppler Feature Extraction of UAVs Based on Synchrosqueezed Transform and Ridge Path Regrouping. In: Liang, Q., Wang, W., Liu, X., Na, Z., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2022. Lecture Notes in Electrical Engineering, vol 873. Springer, Singapore. https://doi.org/10.1007/978-981-99-1260-5_3
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DOI: https://doi.org/10.1007/978-981-99-1260-5_3
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