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Using complex database of satellite malfunctions within the period of 1974–1994 and cosmic ray activity indices, calculated by means of high mountain Alma-Ata neutron monitor data it was shown that malfunction frequency increases during seven days after increase of cosmic ray activity indices. It is significant for high altitude satellite with altitude more than 1000 km.

Taiji-1’s in-orbit magnetic property is significant for the improvement of the satellite’s attitude-control performance and the acceleration noise model of gravitational reference sensor. Test data of satellite drifts have been used to construct the model including interaction among the magnetic field; remnant magnetic moment and induced magnetic moment so as to estimate the satellite’s magnetic property. Using the global optimization method, the remnant magnetic moment of Taiji-1 is estimated to be (-1.42 -0.19 -0.06) Am².

Recent development in the applications of high temperature superconductor (HTS) filters is introduced. Breakthrough had been made in ultra selective band-pass filter with extremely small fractional bandwidth for 3G mobile base stations. Satisfactory results were achieved in the space qualification mechanical tests of the HTS filters. Field trail of the meteorological radar showed that with HTS subsystem the sensitivity and anti-interference ability of the radar were greatly improved.

Antenna fingerprinting is critical for a range of physical-layer wireless security protocols to prevent eavesdropping. The fingerprinting process exploits manufacturing defects in the antenna that cause small imperfections in signal waveform, which are unique to each antenna and hence device identity. It is an established process for physical-layer wireless authentication with proven usage systems in terrestrial systems. The premise relies on accurate signal feature discovery from a large set of similar antennas and stable fingerprint patterns over the operational life of the antenna. However, in space, many low-cost satellite antennas suffer degradation from atomic oxygen (AO). This is particularly a problem for nano-satellites or impromptu temporary space antennas to establish an emergency link, both of which are designed to operate for a short time span and are currently not always afforded protective coating. Current antenna fingerprinting techniques only use Support Vector Machine (SVM) and Convolutional Neural Networks (CNNs) to take a snap-shot fingerprint before degradation, and hence fail to capture temporal variations due to degradation. Here, we show how we can perform robust antenna fingerprinting (99.34% accuracy) for up to 198 days under intense AO degradation damage using Recurrent Neural Networks (RNNs). We compare our RNN results with CNNs and SVM techniques using different signal features and for different Low-Earth Orbit (LEO) satellite scenarios. We believe this initial research can be further improved and has real-world impact on physical-layer security of short-term nano-satellite antennas in space.

DAMPE (DArk Matter Particle Explorer) is a satellite-born experiment promoted by the Chinese Academy of Sciences, with the collaboration of Italian and Swiss agencies. Since December 2015, DAMPE flies at the altitude of 500 km and collects data smoothly. The detector is made of four sub-detectors: top layers of plastic scintillators, a silicontungsten tracker, a BGO calorimeter (32 radiation lengths), and a bottom boron-doped scintillator to detect delayed neutrons. The main goal of the experiment is the search for indirect signals of Dark Matter in the electron and photon spectra with energies up to 10 TeV. Furthermore DAMPE studies cosmic charged and gamma radiation. Moreover, the calorimeter depth and the large acceptance allow to measure cosmic ray fluxes in the range from 20 GeV up to hundreds of TeV with unprecedented precision. An overview of the latest results about the charged cosmic rays will be presented.