Yanlin Sui
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Yanlin Sui has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
- Tao Yu
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2 shared publications - Zhi Wang
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2 shared publications Bin He
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
1 shared publication- Ke Xue
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
1 shared publication - Longqi Wang
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
1 shared publication Tianjiao Fu
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
1 shared publication
Latest Publications
- Open Access
Beat-Notes Acquisition of Laser Heterodyne Interference Signal for Space Gravitational Wave Detection
In space gravitational wave detection missions, the laser heterodyne interference signal (LHI signal) has a high-dynamic characteristic due to the Doppler shift. Therefore, the three beat-notes frequencies of the LHI signal are changeable and unknown. This may further lead to the unlocking of the digital phase-locked loop (DPLL). Traditionally, fast Fourier transform (FFT) has been used as a method for frequency estimation. However, the estimation accuracy cannot meet the requirement of space missions because of the limited spectrum resolution. In order to improve the multi-frequency estimation accuracy, a method based on center of gravity (COG) is proposed. The method improves the estimation accuracy by using the amplitude of the peak points and the neighboring points of the discrete spectrum. For different windows that may be used for signal sampling, a general expression for multi-frequency correction of the windowed signal is derived. Meanwhile, a method based on error integration to reduce the acquisition error is proposed, which solves the problem of acquisition accuracy degradation caused by communication codes. The experimental results show that the multi-frequency acquisition method is able to accurately acquire the three beat-notes of the LHI signal and meet the requirement of space missions.
Open AccessBeat-Notes Acquisition of Laser Heterodyne Interference Signal for Space Gravitational Wave Detection
In space gravitational wave detection missions, the laser heterodyne interference signal (LHI signal) has a high-dynamic characteristic due to the Doppler shift. Therefore, the three beat-notes frequencies of the LHI signal are changeable and unknown. This may further lead to the unlocking of the digital phase-locked loop (DPLL). Traditionally, fast Fourier transform (FFT) has been used as a method for frequency estimation. However, the estimation accuracy cannot meet the requirement of space missions because of the limited spectrum resolution. In order to improve the multi-frequency estimation accuracy, a method based on center of gravity (COG) is proposed. The method improves the estimation accuracy by using the amplitude of the peak points and the neighboring points of the discrete spectrum. For different windows that may be used for signal sampling, a general expression for multi-frequency correction of the windowed signal is derived. Meanwhile, a method based on error integration to reduce the acquisition error is proposed, which solves the problem of acquisition accuracy degradation caused by communication codes. The experimental results show that the multi-frequency acquisition method is able to accurately acquire the three beat-notes of the LHI signal and meet the requirement of space missions.
- Open Access
Analysis of a Capacitive Sensing Circuit and Sensitive Structure Based on a Low-Temperature-Drift Planar Transformer
In space gravitational-wave-detection missions, inertial sensors are used as the core loads, and their acceleration noise needs to reach at a frequency of , which corresponds to the capacitive sensing system; the capacitive sensing noise on the sensitive axis needs to reach . Unlike traditional circuit noise evaluation, the noise in the frequency band is dominated by the thermal noise and the noise of the device, which is a challenging technical goal. In this paper, a low-frequency, high-precision resonant capacitor bridge method based on a planar transformer is used. Compared with the traditional winding transformer, the developed planar transformer has the advantages of low temperature drift and low noise. For closed-loop measurements of capacitive sensing circuits and sensitive structures, the minimum capacitive resolution in the time domain is about , which is far lower than the scientific measurement resolution requirement of for gravitational wave detection. The capacitive sensing noise is converted to in the frequency band of . Although there is a gap between the closed-loop measurement results and the final index, the measurement environment is an experimental condition without temperature control on the ground; additionally, in China, the measurement integrity and actual measurement results of the capacitive sensing function have reached a domestic leading level. This is the realization of China’s future space gravitational wave exploration.Open AccessAnalysis of a Capacitive Sensing Circuit and Sensitive Structure Based on a Low-Temperature-Drift Planar Transformer
In space gravitational-wave-detection missions, inertial sensors are used as the core loads, and their acceleration noise needs to reach at a frequency of , which corresponds to the capacitive sensing system; the capacitive sensing noise on the sensitive axis needs to reach . Unlike traditional circuit noise evaluation, the noise in the frequency band is dominated by the thermal noise and the noise of the device, which is a challenging technical goal. In this paper, a low-frequency, high-precision resonant capacitor bridge method based on a planar transformer is used. Compared with the traditional winding transformer, the developed planar transformer has the advantages of low temperature drift and low noise. For closed-loop measurements of capacitive sensing circuits and sensitive structures, the minimum capacitive resolution in the time domain is about , which is far lower than the scientific measurement resolution requirement of for gravitational wave detection. The capacitive sensing noise is converted to in the frequency band of . Although there is a gap between the closed-loop measurement results and the final index, the measurement environment is an experimental condition without temperature control on the ground; additionally, in China, the measurement integrity and actual measurement results of the capacitive sensing function have reached a domestic leading level. This is the realization of China’s future space gravitational wave exploration. - 21 February 2019
- Published by Taylor & Francis in International Journal of Remote Sensing
- Vol. 40 (14) , 5530-5543
Energy-based cloud detection in multispectral images based on the SVM technique
In this paper, the energy characteristics of Gabor texture are used for cloud detection in high-resolution multispectral images. First, the satellite remote-sensing image is divided into superpixels using simple linear iterative clustering (SLIC), and then, the energy characteristics of Gabor texture and spectral characteristics are computed by extracting the texture features of the superpixels. The features of the cloud superpixels are used as the learning sample of the support vector machine (SVM) classifier, and a classification model is obtained by training the SVM classifier. Finally, a cloud-detection experiment is conducted for various sensor images with three visible bands and one near-infrared band. The experimental results showed that the proposed method provides an excellent average overall accuracy for thick and thin clouds in a complex background of forests, harbours, snow and mountains. The characteristic parameters of this paper are not limited by the image parameters; thus, they provide good results and universality for various types of sensors.
- 21 February 2019
- Published by Taylor & Francis in International Journal of Remote Sensing
- Vol. 40 (14) , 5530-5543
Energy-based cloud detection in multispectral images based on the SVM technique
In this paper, the energy characteristics of Gabor texture are used for cloud detection in high-resolution multispectral images. First, the satellite remote-sensing image is divided into superpixels using simple linear iterative clustering (SLIC), and then, the energy characteristics of Gabor texture and spectral characteristics are computed by extracting the texture features of the superpixels. The features of the cloud superpixels are used as the learning sample of the support vector machine (SVM) classifier, and a classification model is obtained by training the SVM classifier. Finally, a cloud-detection experiment is conducted for various sensor images with three visible bands and one near-infrared band. The experimental results showed that the proposed method provides an excellent average overall accuracy for thick and thin clouds in a complex background of forests, harbours, snow and mountains. The characteristic parameters of this paper are not limited by the image parameters; thus, they provide good results and universality for various types of sensors.