2021 Vol. 41, No. 3

Display Method:
2021, 41(3): 349-349.
2021, 41(3): 349-349.
2021, 41(3): 350-350.
2021, 41(3): 350-350.
阿联酋、 中国、 美国火星探测器齐聚火星
2021, 41(3): 351-351.
CNES主席展望 2021年空间活动计划
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2021, 41(3): 353-353.
2021, 41(3): 354-354.
2021, 41(3): 354-354.
Research Articles
Statistical Research on the Longitudinal Distribution of Detected Properties of Solar Energetic Particles
QIAN Tianqi, DING Liuguan, ZHOU Kunlun, WANG Zhiwei, ZHU Cong
2021, 41(3): 355-367. doi: 10.11728/cjss2021.03.355
Using the observations from multi-points spacecraft, e.g., SOHO and STEREO, 122 SEP events and associated CMEs during the 24th solar cycle from December 2006 to October 2017 are selected. The longitudinal distributions of SEP characteristics and their relationship with CMEs properties are analyzed, as well as the relation with the event-integrated Fe/O ratio. Results are shown as follows: Large SEP events usually have a lower Fe/O ratio, while those events with high Fe/O have lower CME velocity, mass and kinetic energy, but have faster flux rising speed. The duration Du and peak flux Ip of SEP correlate well with the associated CME velocity positively (correlation coefficient, CC: 0.50 and 0.57). Comparing to the events with a high Fe/O ratio, the events with low Fe/O obviously have much higher correlation coefficients for Du and Ip with CME. The characteristic time TO and TR of SEPs generally increases with the raising of relative longitude, while Du and Ip decrease distinctly with the raising of relative longitude. And the slope K of the SEPs flux enhancing in the onset phase seems to decrease from the east (-90°) to west (90°) relative to the source region. TO shows a negative correlation with CME velocity, mass and kinetic energy in the magnetic well-connected points, while there is no distinct correlation in other poor-connected points. Meanwhile, TR has a positive correlation with CME only in the relative longitude range of [-30°, +30°]. Du and Ip have a stronger correlation with CME velocity in the well-connected condition (CC: 0.60 and 0.75 respectively) than others (0.46 and 0.56). The conclusion reveals that the detection of SEP event and its time profile evolution is not only affected by the associated CME, but also controlled by the relative longitude between the magnetic foot point and the solar eruption source, and for the well-connected points, the detectable SEP event has more high intensity and good positive correlation with its associated CME, which is very important for the space weather prediction of SEP events, especially large or extremely large SEP events. Moreover, the SEP event with a high Fe/O ratio seems to become weaker among the relationship with CME, which implies that some facts such as flare acceleration, seed population, and so on, will play important roles during the generation of gradual SEP events associated with CME-driven shock.
Research on Solar Proton Event in the 23rd Solar Cycle Using the Machine Learning Methods
XIONG Senlin, LI Xinlu, FANG Shaofeng, ZOU Ziming
2021, 41(3): 368-374. doi: 10.11728/cjss2021.03.368
Solar Proton Event (SPE) can pose crucial risks to the spacecraft. It is meaningful to analyze and build the relationships between SPE and the associated Coronal Mass Ejection (CME) and solar flares. In this study, the SPE in the 23rd solar cycle is investigated by using machine learning methods. Datasets were constructed based on CME and the solar proton events lists from 1997 to 2006 from the CDA web database. Apriori algorithm are used to survey the correlations between SPEs and the characteristics of flares and CME. The results show that X class flares, full halo CME, high speed (greater than 1000km·-1) CME, and western flares are the four characteristics that most likely to be associated with SPE. The corresponding probabilities are 0.366, 0.355, 0.30 and 0.155. The SPE probabilities at the condition of more than one (CME or flare) features occurring simultaneously were exhibited as well. Using the over sampled CME and flares features, five SPE prediction models are built through five different supervised machine learning algorithms, thus Logistic Regression, Support Vector Classification, K-nearest neighbor, Random Forest and Gradient Boosting Decision Tree. The models all present pretty good prediction accuracy (>0.94), precision (>0.96) and recall rate (>0.91).
Automatic Identification of Magnetopause Crossing Events
SONG Xiaojian, ZUO Pingbing, ZHOU Zilu
2021, 41(3): 375-383. doi: 10.11728/cjss2021.03.375
The magnetopause is the key area of mass, momentum and energy coupling between the solar wind and the magnetosphere. The Magnetopause Crossing Events (MCEs) are usually identified by visual inspection of the plots, which is labor intensive and inefficient. Here we develop a novel procedure that is able to rapidly identify MCEs around the subsolar point and accurately define the transition layer between the magnetosphere and the magnetosheath. Here we synthetically consider the characteristics of the variations of the magnetic field and the particle flux for the identification criteria so that false identifications are avoided to the greatest possible. To demonstrate the efficiency of this procedure, it is applied to the THEMIS observations from 2007 to 2018 when THEMIS's apogee is near the subsolar point. The procedure successfully determines 16758MCEs in about 6 hours on a common PC. The huge number of identified samples of MCEs would benefit the investigations on the magnetopause-related scientific problems, such as indentation of the magnetopause, solar wind-magnetosphere interaction, magnetic reconnection process, and so on. The accuracy and limitation of this algorithm are also analyzed in this paper.
Magnetic Storms Accompanied with Steady Magnetospheric Convection and Characteristics of the Ring Current during the Storms
TI Shuo, SHEN Chao, CHEN Tao, ZENG Gang
2021, 41(3): 384-391. doi: 10.11728/cjss2021.03.384
In this paper,12 magnetic storms accompanied with Steady Magnetospheric Convection (SMC) were selected from 2001 to 2017 based on our new criterion. It was found that these magnetic storms have the same characteristics: a long main phase up to about 10 hours; a minimum platform period for each of their SYM-H, which lasts about 3 to 10 hours; when these magnetic storms occur, the partial ring current is located at the dusk-side constantly, and its duration is equal to the stable southward driving time of the Bz component of IMF. In addition, the ion loss time during its platform period was calculated, though there were some differences in the lifetime of the ions in different events, the lifetime of the ions in our events is much longer than models. And there is no obvious relationship between the lifetime of the ions and the length of the platform period. Based on our study, the decay of ring current is slowed down as the the SMC event during the magnetic storm brings more energy.
Prediction of Equatorial Electrojet Based on the Neural Network during Quiet Time
ZHENG Zhichao, ZHANG Kedeng, WAN Xin, HE Yangfan, YU Lei, SUN Luyuan, GAO Jie, ZHONG Yunfang
2021, 41(3): 392-401. doi: 10.11728/cjss2021.03.392
In this study, BP neural network technology was used to predict the variations of Equatorial Electrojet (EEJ) of Indian sector, Peruvian sector and CHAMP satellite during the magnetic quiet pe-riod after 2008. The neural network training data is the corresponding observation data of EEJ during the period of magnetic quiet from 2000 to 2007. The input parameters are day of year, local time, solar zenith angle, solar activity index (F10.7), lunar age and satellite geographic longitude, and the output parameters are EEJ. The EEJ prediction results are statistically analyzed and compared with the observation results. Results show that: BP neural network has good ability in predicting the variations of EEJ in the event, and the prediction results can reflect the important distribution characteristics of EEJ; there is very good correlation between the predicted values and the observed values of EEJ, and the correlation coefficient between the observed values and the predicted values of geomagnetic sta-tions can reach over 85%. In addition, the prediction results of BP neural network model are compared with those of Yamazaki's empirical model, and the performance of BP neural network is equivalent with Yamazaki's empirical model. The results show that BP neural network has excellent performance in predicting EEJ variations during quiet period, and has a good application prospect.
Automatic Recognition of Solar Active Regions Based on Real-time SDO/HMI Full Disk Magnetograms
CUI Yanmei, LIU Siqing, SHI Liqin
2021, 41(3): 402-410. doi: 10.11728/cjss2021.03.402
Solar Active Regions (ARs) are sources of solar powerful eruptions. The characteristics of ARs are important factors for forecasting solar flares. The Space-weather HMI Active Region Patch (SHARP) is one of the key observations to derive physical properties and to develop solar eruption prediction models. Based on the real-time HMI full disk image, by referring to the computational method developed by Ref.[1] which involves intensity thresholding, morphological analysis and region growing. By comparing our results against those results from Solar Region Summary compiled by NOAA/SWPC during the time interval 2010—2018, it is found that the daily numbers of ARs recognized are in good agreement with the SWPC AR numbers, and their corresponding correlation coefficient is 0.87. On the whole, the total number of ARs recognized is less than the corresponding SWPC AR number. Most of the undetected regions are of small areas, weak magnetic fields and simple magnetic type, which can hardly produce any powerful eruptions. Hence, this study can provide real time data of ARs for forecasting of solar eruptions.
Interpolation Algorithm of Global Ionospheric Map Product TEC
QU Renchao, MIAO Hongli, GOU Ruikun, MAO Peng
2021, 41(3): 411-416. doi: 10.11728/cjss2021.03.411
Global Ionospheric Map (GIM) is an important ionospheric data product provided by the IGS working group, which can provide global real-time ionospheric delay error correction for satellite altimeters. In this study, temporal and spatial interpolation of Total Electron Content (TEC) that derived from GIM data products was performed, with the temporal and spatial resolution of Jason-3 altimeter. Two spatial interpolation methods, Kriging interpolation and Bilinear interpolation, were used in this study. The TEC obtained by these interpolation methods is compared and analyzed with the TEC value that converted from the dual-frequency delay correction of the smoothed Jason-3 altimeter cycle80 data. Results show that the mean bias between Kriging interpolation and processed dual-frequency delay correction is 0.94TECU, the root mean square error is 2.73TECU and the correlation coefficient is 0.91. As a contrast, these statistics between Bilinear interpolation and processed dual-frequency delay correction are 1.43TECU, 6.85TECU, and 0.61, respectively. This demonstrates that the accuracy of the Kriging interpolation is significantly higher than that of the Bilinear interpolation.
High Precision Algorithm for Ionospheric VTEC Based on Single Ground-based GNSS Station
LIU Kun, SHENG Dongsheng, WANG Feifei, ZHANG Hongbo, LI Jianru
2021, 41(3): 417-424. doi: 10.11728/cjss2021.03.417
Using the dual frequency GNSS observation data provided by IGS, the problems existing in Vertical Total Electron Content (VTEC) calculation using Kalman filtering method were analyzed, Kriging-Kalman algorithm was proposed, and the VTEC calculated by the two methods were compared. The results showed that: in the low latitude region, when the number of satellites in observation changed, the VTEC value calculated by Kalman filter method might have curve fracture anomaly; the VTEC value calculated by Kriging-Kalman method changed smoothly relatively. In addition, the changes of VTEC calculated by two method above during the flare were compared, it found that the change of VTEC calculated by Kalman filtering method was smaller than the increment of VTEC caused by flare, while the result of Kriging-Kalman method was more consistent with the actual change. All the results show that the accuracy of VTEC calculated using Kriging-Kalman method is higher in low latitude area, which can reflect the change of VTEC in abnormal space weather activities more accurately, and conducive to the daily accurate monitoring and engineering application of ionospheric VTEC.
A Weight Based Hierarchical Vector Quantization Algorithm for Space Environment Volume Data
BAO Lili, CAI Yanxia, LIN Ruilin, LIU Siqing, SHI Liqin, CAO Yong
2021, 41(3): 425-430. doi: 10.11728/cjss2021.03.425
Visualization has been widely applied in space environment domain. However, compressed volume rendering algorithms based on VQ are concerned on fidelity and compression rate, not combined with specific application. To fulfill the specific visualization requirements for space environment volume data, an application-driven compression and rendering algorithm is proposed, which is Weight Based Hierarchical Vector Quantization (WHVQ). The volume data is initially partitioned into disjoint 43 blocks. Weights are assigned to the blocks according to their importance. The blocks are then decomposed into a three level hierarchical representation and each block is represented by a mean value and two detail vectors. To the top two levels, a splitting based on principal component analysis and weight is adopted to form their initial codebooks. Then, LBG algorithm based on weight is conducted for codebook refinement and quantization. The experimental results show that WHVQ is able to improve the quality of reconstruction in interested area on the premise of the good overall fidelity.
Mirror-mode Wave Identification Methods and Their Application to Martian Magnetosheath
JIN Taifeng, LI Lei, ZHANG Yiteng
2021, 41(3): 431-438. doi: 10.11728/cjss2021.03.431
Mirror-mode waves are structures usually seen in plasma with temperature anisotropy, identifiable through features in magnetic field and particle distribution and fluctuation. Two identification methods are analyzed and compared in this paper. Method A uses magnetic field data only, while Method B combines magnetic field and particle data. Method A is based mainly on features of magnetic field variation such as large amplitude fluctuation along background field direction, using magnitude of magnetic field fluctuation ΔB/|B| and angles between background field and maximum/minimum variation direction θmax, θmin as criteria. Method B is based on features such as wave compression, total pressure balance and zero velocity in plasma frame. Identification using data from MAVEN probe in the Martian magnetosheath shows that Method A can cause misidentification under certain circumstances, e.g. magneto-sonic waves. Results of identification using Method A with varying criteria ΔB/|B| and θmin/θmax are studied in the Martian magnetosheath, suggesting threshold values: θmin> 40°, θmax< 40° and ΔB/|B| > 80% can yield satisfying results.
Radiation Dose of LND on the Lunar Surface in Two Years
ZHANG Shenyi, HOU Donghui, WIMMER-SCHWEINGRUBER R F, SUN Yueqiang, WANG Chunqin, CHANG Zheng, XU Zigong, SHEN Guohong, YUAN Bin, XUE Changbin
2021, 41(3): 439-444. doi: 10.11728/cjss2021.03.439
The radiation dose on the lunar surface is an important parameter affecting the safety of astronauts and the residence time of the lunar surface. The measurement of the particle radiation on the lunar surface can provide an important basis for the radiation safety protection of astronauts. Based on the two-year observation data of lunar neutron and radiation dose detector on Chang'E-4 lander, the average total absorbed dose rate of lunar particle radiation in silicon is 12.66±0.45μGy·h-1, and the absorbed dose rate of neutral particle is 2.67±0.16μGy·h-1. The radiation dose rate decreases slowly with time, but the change of LET spectrum is very small. The decrease of radiation dose rate due to the decrease of fubusch of GCR at the end of solar activity in December 2020 was observed.
Research Progress of Space Mice Flight Payload
LI Jie, LIU Fangwu, ZHANG Tao
2021, 41(3): 445-456. doi: 10.11728/cjss2021.03.445
Rodents represent one of the most important animal models in space biology experiments. Compared to other animals, the mice could better adapt to weightless conditions in space. Consequently, more and more researchers focus on the study of space mice flight payload. In the capsule, the mice would undergo a series of magical changes in the physiological behavior, the bone, and the nervous system. The experiments have shown that the research about these changes might contribute to the diagnostic of astronauts health, such as muscle atrophy. It is reported that many space mice experiments have been carried out abroad. However, China has not yet had sufficient research in this field. In order to address the problem, a large number of relevant literature were surveyed in this work. The development of various mice flight payloads and the content of the experiment were summarized in this paper. The specific contents are as follows. Firstly, the technology of mice culture on the ground was introduced, which gives a reference for the design of the flight payload. Then, five kinds of existing flight payloads abroad were discussed. Finally, the proposal for the development of domestic mice flight payload was proposed.
Analysis of Celestial Gravity Influence on Heliocentric Formation Flying of Gravitational Wave Observatory
LI Zhuo, ZHENG Jianhua, LI Mingtao, YU Xizheng, WANG Youliang
2021, 41(3): 457-466. doi: 10.11728/cjss2021.03.457
A mathematical model of celestial gravity influence on heliocentric formation flying of gravitational wave observatory is established for Taiji in this paper. Influences of planets, the Moon, dwarf planets and asteroids in the solar system on heliocentric formation flying of gravitational wave observatory are analyzed by simulation. To analyze the influence of asteroids on the stability of constellation, a double screening method is proposed, which takes the orbit distance and magnitude of asteroids into consideration comprehensively. The method avoids a large number of calculations on asteroids and is able to quickly estimate the influence of the relative acceleration of asteroids on constellation. The influences of initial phase angles on heliocentric formation-flying satellites are also analyzed. Simulation results show that the Earth, the Venus and the Jupiter have great influences on heliocentric formation flying of gravitational wave observatory, and their cumulated relative acceleration is -2.78×10-11km·-2. The relative acceleration caused by dwarf is 1.25×10-17km·-2. The relative acceleration caused by asteroids is 1.1180×10-15km·-2. Moreover, influences of gravity perturbations of solar system bodies on formation-flying satellites are insensitive to initial phase angles.
Research on the Multidimensional Data Cube Method of the Quantum Science Experiment Satellite
GUO Guohang, LI Hu, HU Tai, XIE Xiajie, ZHAN Fenglin
2021, 41(3): 467-474. doi: 10.11728/cjss2021.03.467
Scientific experiment satellite should be target-oriented, which requires several mission teams to develop a phase experiment plan and take operations according to the actual situation. These experiment plans depend on the data generated by mission operation and are integrated from the strategy set derived from some data analysis of each subsystem of the scientific satellite mission. Along with the operation of QUESS on orbit, a large amount of operational data will be generated. To solve this problem, current mainstream approach mainly relies on log statistics and data statistics of conventional database systems. However, these methods consume more energy and time, and require more professional skills of analysts, which cannot meet the requirements of multi-angle and multi-granularity research and judgment tasks. Moreover, the scalability of the methods is very poor. When the observation angle of the problem changes, it is often necessary to reorganize the statistical analysis of the data. In view of the above situations, a multi-dimensional data modeling and analysis method based on data cube is proposed, which can face different topics and support multi-level, multi-angle and multi-granularity statistical analysis of data, providing good support for decision makers.
Design of GNSS Remote Sensing Satellite Constellation
WANG Jueyao, FU Yang, BAI Weihua, WEI Shilong, GUO Bibo, YAN Feng, XIE Chengqing
2021, 41(3): 475-482. doi: 10.11728/cjss2021.03.475
Global Navigation Satellite System (GNSS) remote sensing can provide irreplaceable atmospheric sounding data based on its sounding technology. But the research on satellite constellation design for GNSS remote sensing is relatively backward. In-orbit resources have not been fully utilized, and the design of sounding satellite constellation lacks systematic and theoretical support. Under the assumption of ideal atmosphere model, the effect of configuration parameters of sounding constellation on sounding performance is studied by geometric analysis method. With 200km×200km×6h as the reference scale, the design criteria for the new generation of GNSS remote sensing sounding satellite constellation are established. Four of FY-3 satellites are combined to make GNSS remote sensing satellite constellation optimization design results under three kinds of constellation configurations. The results show that the design criteria are feasible and instructive. In combination with the FY-3 satellites, three Walker sub-constellations with inclination of 68°, 60° and 24° have the best performance.
Automatic Balancing Control of Air-bearing Simulator Based on Firefly Algorithm Improved Neural Network
ZHOU Guoguang, JIN Guang, XU Wei, PIAO Yongjie, CHANG Lin
2021, 41(3): 483-490. doi: 10.11728/cjss2021.03.483
In order to accurately reproduce the multi-satellite networking technology and simulate the multi-mode high-resolution imaging process on the ground, the three-axis air-bearing test bed was the key device of simulation. In this paper, a fast automatic balance adjustment control algorithm was proposed based on firefly algorithm improved BP (Back Propagation) neural network PID (Proportion Integration Differentiation) control. Aiming at the problem of long adjustment time and easy to obtain a non-optimal solution, the firefly algorithm was introduced to optimize the initial weight and threshold value of the BP neural network, and improve the algorithm performance in convergence rate and stability. Based on the kinematics and dynamics model of the three-axis air-bearing simulator platform, the simulation results show that the optimized algorithm reduces the x-axis centroid offset to 2.3×10-7m in 3.1s. The algorithm has faster and higher stability on air-bearing simulator automatic balancing control, and satisfies the demand for multi-satellite imaging process simulation.
Temperature Prediction of Satellite Flywheel Based on LightGBM
ZHU Jiaxi, LIU Yurong
2021, 41(3): 491-498. doi: 10.11728/cjss2021.03.491
In order to ensure the stable operation of satellites, it is important for the ground system to monitor and predict the satellite state, especially the monitoring of flywheel temperature. As an important component of attitude control system of a satellite, the temperature of flywheel is important to identify the state of the system. The prediction of flywheel temperature is of great significance to the stable operation of satellites in orbit. In this paper, based on the LightGBM machine learning framework, a gradient boosting decision tree model is established by using spatial environmental data and in-orbit telemetry data of a satellite, to predict the temperature change of satellite flywheel. By comparing with the actual flywheel temperature, the prediction accuracy can meet the monitoring requirement of satellite flywheel temperature. This model can be applied to warn the ground system the possible temperature anomalies of attitude control system, so that controllers can avoid risks ahead of time and ensure the safe operation of satellites. The research results have certain universality for other satellite flywheel systems.
Long-term Variation of Differential Code Biases of Ionospheric TEC Monitor Based on Hardward Signal Simulator
LIU Yiwen, ZHANG Zhenzhong, OU Ming
2021, 41(3): 499-504. doi: 10.11728/cjss2021.03.499
Hardware signal simulator can be used to calibrate the hardware delay of the ionospheric TEC monitor. In this paper, the long-term change of DCB derived by hardware calibration method is analyzed, by two independent calibration experiments (with a time interval of nearly 41.5 months) on the same receiver (for GPS signals). The results show that the mean DCB value of the receiver increases from 16.122ns in the first experiment to 16.749ns in the second experiment. It increases 0.627ns in about 41.5 months. The monthly increment of DCB is about 0.0151ns. The standard deviation of DCB increases slightly from 0.05ns to 0.07ns between the two experiments. In addition, the TEC calibration accuracy (Root Mean Square Error) of both two experiments reach about 0.3TECU, and the corresponding DCB errors reach about 0.1ns. It indicates that the DCB variation between different channels is quite consistent. In the second experiment, the TEC measurement error will increase to about 1.8TECU if using the DCB value obtained in the first experiment. The monthly increment of TEC error is about 0.0434TECU.
Study on Satellite-to-ground Laser Communications with Existence of Atmosphere
LI Hu, HU Tai, SHAO Shiyong, WU Pengfei
2021, 41(3): 505-510. doi: 10.11728/cjss2021.03.505
The laser beam used to establish a communication channel between satellite and ground segments has a small divergence angle and a tiny spot on the Earth’s surface, which may lead to the fail of the system. So it’s important to study the deflection of laser beam by the Earth’s atmosphere and find a way to calibrate this error. Both theoretical analysis and real data processing method are used to obtain the mathematical model for divergence angle of laser communication beam and its correction function. Then the model has been applied to the data, which was used to describe the atmosphere state by traditional ground segments to obtain the critical elevation angle. According to the results of calculation, our conclusion will be that the correction should be done when the critical elevation happens.
Efficient Correction Method for Polarimetric Distortion Error of Polarimetric Scatterometer
HU Jiwei, REN Hongxuan, LÜ Ailing, DANG Hongxing, TAN Xiaomin
2021, 41(3): 511-518. doi: 10.11728/cjss2021.03.511
The full-polarization scatterometer is a new type of microwave scatterometer that can simultaneously measure the co-polarization and cross-polarization backscatter of the target. It can solve the wind direction ambiguity problem of the traditional scatterometer in the sea surface wind retrieval and improve the wind measurement accuracy. Moreover, the cross-polarization backscatter can effectively increase the sea surface wind speed measurement range and can be used for typhoon monitoring. High-precision sea surface wind retrieval using full-polarization scatterometer data first needs to correct the polarization distortion error of the full-polarization scatterometer system. To solve this problem, the polarimetric scattering coefficient model influenced by polarimetric distortion error is built based on the signal model of polarimetric scatterometer, and then the influence of polarimetric distortion error in quantitatively analyzed. Based on the polarimetric scattering coefficient model, some assumptions of ocean scattering characteristic and polarimetric calibration are introduced to establish the correction model of polarimetric scattering coefficients. Simulation data based on RADARSAT-2 polarimetric scattering coefficients of different sea region is corrected and results show that the proposed method can effectively correct of polarimetric distortion error and greatly improve the measurement accuracy of polarimetric scattering coefficients.