Micro motion parameter inversion of spatial cone target based on convolutional neural networks

Bo Li; Hongmei Ren; Zhihe Xiao

doi:10.1117/12.2617301

15 February 2022 Micro motion parameter inversion of spatial cone target based on convolutional neural networks

Bo Li, Hongmei Ren, Zhihe Xiao

Proceedings Volume 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021); 121664B (2022) https://doi.org/10.1117/12.2617301
Event: Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 2021, Hong Kong, Hong Kong

Abstract

The inversion of the micro motion parameters of the spatial cone target is of great significance for the detection and recognition of the spatial target. In this paper, the inversion of micro motion parameters of cone target is studied, Convolutional Neural Networks(CNN) training for time-frequency image is proposed. Different precession angles of target are classified as different categories. According to the classification results, the precession angle parameters of target are inversed. The simulation results show that the coiler neural network can invert the precession angle of the micro-motion target and has a good inversion effect.

Citation Download Citation

Bo Li, Hongmei Ren, and Zhihe Xiao "Micro motion parameter inversion of spatial cone target based on convolutional neural networks", Proc. SPIE 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 121664B (15 February 2022); https://doi.org/10.1117/12.2617301

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