Development of multi-functional composite structures with embedded electronics for space application

Conventional spacecraft structural function has been limited to supporting loads and mounting avionics only. In contrast, the technology of ‘multi-functional structures’ can integrate thermal and electronic functions into the spacecraft’s inherent load-bearing capability. In addition, sufficient radiation shielding effectiveness can be provided for the anticipated mission environment. Utilizing this concept, the ratio of electrical functionality to spacecraft volume can be dramatically increased and significant mass savings can be obtained. In this paper, spacecraft electronics are miniaturized using advanced IT applications such as flexible circuitry, miniaturized components, featherweight connectors, and so on, that they can be easily embedded within a structural panel. A sandwich structural panel consists of an aluminum honeycomb core and lightweight CFRP facesheets. Integration of electronics is implemented within the panel by mounting electronics on a multi-layered composite enclosure with multi-materials. This composite enclosure provides a load-bearing, effective thermal conduction, radiation shielding capabilities and an available space for embedding electronics. A series of environmental tests and analyses is carried out to demonstrate that the flight hardware is qualified for the expected mission environments. This approach will be utilized for the advanced small satellite ‘STSAT-3’ to validate the multi-functional structures concept.     

Measuring the economic benefits of an environmental monitoring satellite project: The value of information approach

This paper reports a first application of contingent valuation method to measure the value of information generated by earth science data from an environmental geostationary satellite payload called Geostationary Environmental Monitoring Satellite. The purpose of the space project is to improve the accuracy of air pollution information by enhancing air pollution monitoring and forecasting system coupled with conventional ground level monitoring stations located throughout South Korea.     

The X-Ray Spectrometer on the MESSENGER Spacecraft

NASA’s MESSENGER (MErcury Surface, Space ENvironment, GEochemistry, and Ranging) mission will further the understanding of the formation of the planets by examining the least studied of the terrestrial planets, Mercury. During the one-year orbital phase (beginning in 2011) and three earlier flybys (2008 and 2009), the X-Ray Spectrometer (XRS) onboard the MESSENGER spacecraft will measure the surface elemental composition. XRS will measure the characteristic X-ray emissions induced on the surface of Mercury by the incident solar flux. The Kα lines for the elements Mg, Al, Si, S, Ca, Ti, and Fe will be detected. The 12° field-of-view of the instrument will allow a spatial resolution that ranges from 42 km at periapsis to 3200 km at apoapsis due to the spacecraft’s highly elliptical orbit. XRS will provide elemental composition measurements covering the majority of Mercury’s surface, as well as potential high-spatial-resolution measurements of features of interest. This paper summarizes XRS’s science objectives, technical design, calibration, and mission observation strategy.     

The Energetic Particle and Plasma Spectrometer Instrument on the MESSENGER Spacecraft

The Energetic Particle and Plasma Spectrometer (EPPS) package on the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission to Mercury is composed of two sensors, the Energetic Particle Spectrometer (EPS) and the Fast Imaging Plasma Spectrometer (FIPS). EPS measures the energy, angular, and compositional distributions of the high-energy components of the in situ electrons (>20 keV) and ions (>5 keV/nucleon), while FIPS measures the energy, angular, and compositional distributions of the low-energy components of the ion distributions (<50 eV/charge to 20 keV/charge). Both EPS and FIPS have very small footprints, and their combined mass (∼3 kg) is significantly lower than that of comparable instruments.     

Solution and performance analysis of geolocation by TDOA

One method of geolocation is based on measuring the time difference of arrivals (TDOAs) of a signal received by three or four geostationary satellites. The received signals are cross-correlated to determine the TDOAs and a set of nonlinear equations are solved to produce the location estimate. An exact solution for the transmitter position is derived for the three or four receiver cases. Extension of the solution method to more receivers is straightforward. An analysis of the performance of the system is given, together with expressions for predicting the localization mean-square errors (MSEs) and bias, and the Cramer-Rao bound. Both precision in TDOA measurements and the relative geometry between receivers and transmitter affect the localization accuracy. The geometric factors act as multipliers to the TDOA variance in the bias and MSE formulae. A study of the dependency of the geometric factors on transmitter position and satellite spacings are provided, as well as simulation results     

Forecasting space weather: Predicting interplanetary shocks using neural networks

We are developing a system to predict the arrival of interplanetary (IP) shocks at the Earth. These events are routinely detected by the Electron, Proton, and Alpha Monitor (EPAM) instrument aboard NASA’s ACE spacecraft, which is positioned at Lagrange Point 1 (L1). In this work, we use historical EPAM data to train an IP shock forecasting algorithm. Our approach centers on the observation that these shocks are often preceded by identifiable signatures in the energetic particle intensity data. Using EPAM data, we trained an artificial neural network to predict the time remaining until the shock arrival. After training this algorithm on 37 events, it was able to forecast the arrival time for 19 previously unseen events. The average uncertainty in the prediction 24 h in advance was 8.9 h, while the uncertainty improved to 4.6 h when the event was 12 h away. This system is accessible online, where it provides predictions of shock arrival times using real-time EPAM data.