Algorithms and Techniques for Environmental Sensing and Spacecraft Monitoring

The space environment is hazardous: harsh radiation in the form of ionized, highly energetic particles and space weather events affect the operation, performance, and lifetime of spacecraft and their instruments. And, space is becoming more populated, with new constellations of several hundreds of small satellites planned over the next decade to provide communications and navigation services upon which society has become increasingly reliant. This drives a need for spacecraft to be able to quickly identify and react to hazards as well a greater need for situational awareness. In addition, satellites need increased autonomy to improve responsivity and reduce the load on human operators. Dedicated instruments to monitor the environment are not always included on spacecraft due to resource constraints. The goal of this work is to enable characterization of the external high-energy radiation environment, monitoring of system performance, and identification of hazards by developing techniques using existing hardware on spacecraft. The research efforts using this grant have been two-fold. In the first part of the work, using spacecraft housekeeping telemetry, we have developed algorithms that identify unusual behavior in satellite health telemetry. Once these events have been identified, we collect and analyze them, along with assessing space weather observations and operational environment factors. Our approach uses transient event detection and change-point event detection techniques that use a sliding window-based median, statistically evaluating the telemetry stream compared to a local norm. This approach allows application of the algorithms to any spacecraft platform because there is no reliance in the algorithms on satellite- or component-specific parameters, and it does not require a priori knowledge about the data distribution. We apply these event detection algorithms to individual telemetry data streams on geostationary Earth orbit (GEO) communications satellites (ComSats), examining telemetry from solid-state power amplifiers and amplifier thermistors from 32 GEO ComSats from 1991 to 2015, resulting in a compiled list of unusual events for each satellite. This approach identifies up to six events that affect 51 of 53 telemetry streams at once, indicative of a spacecraft system-level event. In two satellites, the same top event date (4 December 2008) occurs over more than 10 years of telemetry from both satellites. Of the five spacecraft with known maneuvers, the algorithms identify the maneuvers in all cases. Event dates are compared to known operational activities, space weather events, and available anomaly lists to assess the use of event detection algorithms for spacecraft monitoring and sensing of the space environment. In the second part of this work, we have developed a technique to quantitatively characterize the high-energy electron environment using scientific imager radiation “noise”. Solid-state detectors are commonly used as scientific imagers on spacecraft. In addition to being sensitive to incoming photons, semiconductor devices also are affected by incoming charged particles collected during integration and detector readout. These radiation hits from the space environment are typically considered “noise” at the detector. We post-process raw images to obtain frames with only the radiation contribution. The camera settings are used to compute the energy deposited in each pixel, which corresponds to the intensity of the observed radiation hits. The energy deposited in the pixels by incident particles from processed images are compared with the results from 3D Monte Carlo particle transport simulations of the imaging instrument using Geant4. We demonstrate the technique using data from the Solid-State Imaging (SSI) instrument, which is a silicon charge-coupled device (CCD) on the Galileo spacecraft, in orbit around Jupiter from 1996 to 2003. Jupiter has the largest and strongest magnetosphere of all of the planets in the solar system and it is dominated by high-energy electrons. Measuring and characterizing megaelectron volt (MeV) particles is fundamental for understanding the energetic processes powering the magnetosphere, interactions of the particles with surfaces of the Jovian satellites, and the effects of these particles on spacecraft near or in Jovian orbit. Electrons in Jupiter’s magnetosphere can interact with spacecraft and lead to component failures, degradation of sensors and solar panels, and physical damage to materials. Measurements of the high-energy (>1 MeV) electron environment at Jupiter are currently spatially and temporally limited, predominantly coming from the Energetic Particle Detector (EPD) on the Galileo spacecraft. Simulating the response of the SSI instrument to mono-energetic electron environments, we find that the SSI is capable of detecting ≥10 MeV electrons (>90% of <10 MeV particles are stopped with 95% confidence). Using geometric scaling factors computed for the SSI, we calculate the environment particle flux given a number of pixels with radiation hits. We compare the SSI results to measurements from the Galileo EPD, examining the electron fluxes from the >11 MeV integral flux channel. We find agreement with the EPD data within 3-sigma of the EPD data for 43 out of 43 (100%) of the SSI images evaluated. 62% of fluxes are also within 1-sigma of the EPD data. To demonstrate that the general technique is applicable to other imagers, we also analyze the Galileo Near-Infrared Mapping Spectrometer (NIMS). We find that NIMS is sensitive to ≥5 MeV electrons and the calculated fluxes are consistent with the EPD. This approach can be applied to other sets of imaging data (star trackers, etc.) in energetic electron environments, such as those found in geostationary Earth orbit. This work also includes a summary of required and recommended information (tests, models, etc.) for the use of science imagers as high-energy electron sensors.