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J. Eur. Opt. Society-Rapid Publ. 21, 13( 2025)
0.9823, and the regression model was as follows: y = �0.39547 + 0.181115x. Thistrendwasconsistentwith the theoretical result that a larger current correlated to a greater signal intensity; these results could provide a basis for subsequent distance estimation using a constant signal intensity.
5 Conclusions
The addition of flame suppressant substances to the jet fuel of a spacecraft can reduce the intensity of the infrared radiation; thus, the detection of the tail flame in the infrared band is difficult. Therefore, another feasible method involves the identification of the spacecraft tail flame using the characteristic spectrum generated by the excitation of the potassium atoms in the flame suppressant. Due to highly complex radiation noise in the atmospheric background, the weak potassium signal is easily hidden in the strong background spectrum and cannot be directly identified. In this study, an extraction algorithm for the potassium signals in the spatial heterodyne spectrum was proposed using PCA. The results showed that the algorithm could effectively extract the weak signals against a strong background, and simultaneously, the signal intensity had a good linear relationship with the light source current intensity. However, at present, the algorithm cannot completely remove the residual noise signal around the potassium characteristic peak; this could result in the loss of some effective information. Furthermore, the further application of the NLM denoising algorithm effectively addresses the limitations of the PCA method. The experimental results fully confirm the remarkable effectiveness of the PCA-NLM algorithm employed in this paper in terms of accurately extracting target spectral components and efficiently suppressing noise.
Funding
National Key Research and Development Project( 2022YFB3901803), supported by the National Natural Science Foundation of China( 41961050, 41975033), Key Laboratory of General Optical Calibration and Characterization Technology, Chinese Academy of Sciences, Graduate Education Innovation Program of Guilin University of Electronic Science and Technology( 2024YCXS220).
Conflicts of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data availability statement
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
Author contribution statement
XinQiang Wang: Methodology, Investigation, Writing-Original Draft Preparation, Writing – review & editing. SiQian Yang: Conceptualization, Writing – review & editing. Wei Xiong:
Validation, Writing – review & editing. FangYuan Wang: Conceptualization, Validation, Writing – review & editing. Song Ye: Writing – review & editing.
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