Prognostication of Technical Conditions for Low-Orbit Spacecraft with the Use of Neural Networks

An analysis of the typical external factors of a forecasting background is performed for the case when these factors affect the operation of onboard maintenance systems of low-orbit satellites. Taking into account the formulated requirements for the method of forecasting spacecraft characteristics, we have substantiated and tested a neural network prognostic model.     

Fine Resolution Epithermal Neutron Detector (FREND) Onboard the ExoMars Trace Gas Orbiter

ExoMars is a two-launch mission undertaken by Roscosmos and European Space Agency. Trace Gas Orbiter, a satellite part of the 2016 launch carries the Fine Resolution Neutron Detector instrument as part of its payload. The instrument aims at mapping hydrogen content in the upper meter of Martian soil with spatial resolution between 60 and 200 km diameter spot. This resolution is achieved by a collimation module that limits the field of view of the instruments detectors. A dosimetry module that surveys the radiation environment in cruise to Mars and on orbit around it is another part of the instrument.This paper describes the mission and the instrument, its measurement principles and technical characteristics. We perform an initial assessment of our sensitivity and time required to achieve the mission goal. The Martian atmosphere is a parameter that needs to be considered in data analysis of a collimated neutron instrument. This factor is described in a section of this paper. Finally, the first data accumulated during cruise to Mars is presented.