Influence of Satellite Micro-Vibrationon Signal-to-Noise Ratio of Wind LiDAR

Qipeng, 曹启鹏 Cao; Yongchang, 李永昌 Li; Xiaojing, 董小静 Dong; Chao, 王超 Wang; Jing, 王靖 Wang

doi:10.3788/lop57.092802

激光与光电子学进展

2020

DOI: 10.3788/lop57.092802

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Influence of Satellite Micro-Vibrationon Signal-to-Noise Ratio of Wind LiDAR

曹启鹏 Cao Qipeng¹,

李永昌 Li Yongchang²,

董小静 Dong Xiaojing³

et al.

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Source Quantitative Identification by Reference-Based Cubic Blind Deconvolution Algorithm

Luo,

Zhang,

Gong

et al. 2023

Chin. J. Mech. Eng.

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The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference information. However, the separation performance depends largely on the construction of reference signals. To improve the robustness of the semi-blind deconvolution algorithm to the reference signals and the convergence speed, the reference-based cubic blind deconvolution algorithm is proposed in this paper. The proposed algorithm can be combined with the contribution evaluation to provide trustworthy guidance for suppressing satellite micro-vibration. The normalized reference-based cubic contrast function is proposed and the validity of the new contrast function is theoretically proved. By deriving the optimal step size of gradient iteration under the new contrast function, we propose an efficient adaptive step optimization method. Furthermore, the contribution evaluation method based on vector projection is presented to implement the source contribution evaluation. Numerical simulation analysis is carried out to validate the availability and superiority of this method. Further tests given by the simulated satellite experiment and satellite ground experiment also confirm the effectiveness. The signals of control moment gyroscope and flywheel were extracted, respectively, and the contribution evaluation of vibration sources to the sensitive load area was realized. This research proposes a more accurate and robust algorithm for the source separation and provides an effective tool for the quantitative identification of the mechanical vibration sources.

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Source Quantitative Identification by Reference-Based Cubic Blind Deconvolution Algorithm

Luo,

Zhang,

Gong

et al. 2023

Chin. J. Mech. Eng.

View full text Add to dashboard Cite

show abstract

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Influence of Satellite Micro-Vibrationon Signal-to-Noise Ratio of Wind LiDAR

Cited by 1 publication

References 0 publications

Source Quantitative Identification by Reference-Based Cubic Blind Deconvolution Algorithm

Source Quantitative Identification by Reference-Based Cubic Blind Deconvolution Algorithm

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