This high-resolution satellite is equipped with a push-broom high-resolution camera (PMS) that consists of panchromatic, blue, green, red, and near-infrared bands. The Moon is considered an stable light source, unaffected by atmospheric conditions, making it an ideal reference for absolute and relative radiation calibration of remote sensors. To utilize the Moon for calibration purposes, the satellite implemented two specific imaging modes: lunar push broom for absolute radiation calibration and lunar side-slither for relative radiation calibration. The lunar observations conducted by this satellite in orbit were highly successful. In 2019, the satellite conducted lunar observations at various lunar phase angles, while in 2021 and 2022, observations were specifically conducted during the full moon. These observations yielded many effective full lunar disk images. The stability of the PMS camera was analyzed using the band ratio irradiance method. Analysis of the satellite's four-year lunar observation data revealed a strong correlation between the lunar irradiance measured by PMS and the lunar phase angle. The analysis of the band ratio indicated that the multi-spectral bands are stable. However, the PAN band exhibited a tendency to attenuate, with a decay rate of approximately 0.0086 per year.
The existing space-based remote sensing has problems such as weak collaboration, slow response, and long links, which cannot meet the application requirements of real-time anomaly detection, recognition, and transmission. This article studies the characteristics of existing surface anomaly classification, establishes a demand matrix for anomaly remote sensing, establishes a new surface anomaly real-time detection system, and proposes a working mode for anomaly real-time recognition, using the constellation system task and information flow design combined with the on-board intelligent processing unit, improve the anomaly recognition and service capability of the space-based system, design the mission flow and information flow of the constellation system, and finally analyze the communication link and timeliness of the system. The simulation analysis results show that the system can achieve minute level efficient anomaly recognition and early warning, effectively improving the service capability to users, this provides an overall idea and architectural reference for the construction of future space-based surface anomaly real-time detection systems.
In order to improve the fatigue evaluation system of the satellite in the transportation environment, a fatigue analysis method of satellite transportation environment based on the digital twin was explored in this paper. At first, the basic theories and method of fatigue analysis are introduced in detail. The fatigue damages of the satellite in the transportation environment are evaluated by using the random vibration and sinusoidal vibration stress fatigue analysis separately. And then, digital twin fatigue models based on the acceleration response of random vibration and sinusoidal vibration are established. Finally, fatigue models are utilized to analyze the fatigue damage to the satellite in the transportation environment and are compared with the stress fatigue models before. The results show that all the fatigue damage keeps in accordance with each other verifying the accuracy of the fatigue model based on the digital twin presented in this paper.
Global Navigation Satellite System reflectometry (GNSS-R) technology uses the signal receiver to receive the reflected signal of navigation satellite for ground feature inversion. It has the advantages of wide dynamic range, all day, all weather, light weight and low cost. It has a broad application prospect in the field of remote sensing. On June 5, 2019, China's first group of test satellites carrying GNSS-R payload, BF-1 A/B satellites, was successfully launched on the sea by using CZ-11 carrier rocket. GNSS-R data with high spatial and temporal resolution were obtained during the operation of the satellite in orbit. In order to solve the problem of low accuracy and few methods of GNSS-R inversion of sea surface wind speed, this paper proposes a sea surface wind speed inversion method based on the delay doppler map average (DDMA) of BF-1 satellite. Firstly, the GNSS-R sea surface scattering model is established by using Z-V model and Elfouhaily wave spectrum to verify the relationship between the observation of BF-1 satellite and the change of wind speed, Then, the principle of GNSS-R sea surface wind speed inversion is studied. Through the correction and normalization of observations, the inversion observation DDMA is obtained. Finally, the geophysical model function (GMF) is established by using L1 level satellite data to realize the high-precision inversion of sea surface wind speed. The root mean square (RMS) accuracy of wind speed inversion is 1.81m/s, which is slightly higher than that of CYGNSS when compared with that of CYGNSS at the same time. The experimental results show that the inversion trend of the same region and time is the same, which proves the accuracy and effectiveness of the data processing results, it will also provide support for the follow-up GNSS-R satellite development and the development and optimization of surface wind speed inversion algorithm.
In recent years, the emerging global navigation satellite system reflectometry (GNSS-R) technology has become a research hotspot for its lightweight, high sensitivity and rich technology application scenarios. It has broad application prospects in the field of remote sensing detection and navigation technology. The role of GNSS-R remote sensing satellite in the field of marine remote sensing is becoming increasingly prominent. The acquisition of data and information and the observation performance of GNSS-R remote sensing satellite are not only constrained by the remote sensing equipment itself, but also affected by the satellite orbit. Based on the technical characteristics of GNSS-R remote sensing satellite, this paper proposes a grid based coverage efficiency statistical method, analyzes some influencing factors of GNSS-R remote sensing satellite efficiency based on the remote sensing task, and analyzes the influence of each factor on GNSS-R remote sensing satellite efficiency by modeling -It can provide theoretical reference for GNSS-R satellite orbit selection and optimization, onboard load design optimization and large-scale system construction.