Target material recognition with spectral emissivity curve matching method

Chao Qiu; Linag Huang; Jiapeng Wang; Hongsheng Sun; Wanglin Yang; Jidong Du

doi:10.1117/12.2655808

20 January 2023 Target material recognition with spectral emissivity curve matching method

Chao Qiu, Linag Huang, Jiapeng Wang, Hongsheng Sun, Wanglin Yang, Jidong Du

Proceedings Volume 12558, AOPC 2022: Optical Spectroscopy and Imaging; 125580O (2023) https://doi.org/10.1117/12.2655808
Event: Applied Optics and Photonics China 2022 (AOPC2022), 2022, Beijing, China

Abstract

A method of target material recognition based on spectral emissivity curve matching is proposed to solve the problem of target material recognition in complex field environment. In this paper, the target material recognition model of spectral emissivity curve is established, and the effectiveness of the model is verified by simulation experiments. The model input data is the spectral emissivity measurement data of the target material to be measured. The model construction mainly includes weighted deviation maximization model construction, Lagrange function extremum method solution and similarity function construction. Through the simulation experiment model, the similarity between different curves is calculated and the target is effectively identified. The influence of spectral emissivity noise on similarity is analyzed. The target spectral emissivity superposition noise amplitude is 0.01 ~ 0.05 times, and the similarity is greater than 0.6. This method can accurately identify the target material. The spectral emissivity identification method proposed in this paper can provide technical support for target identification in complex

Citation Download Citation

Chao Qiu, Linag Huang, Jiapeng Wang, Hongsheng Sun, Wanglin Yang, and Jidong Du "Target material recognition with spectral emissivity curve matching method", Proc. SPIE 12558, AOPC 2022: Optical Spectroscopy and Imaging, 125580O (20 January 2023); https://doi.org/10.1117/12.2655808

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