Intelligent Sampling of Hazardous Particle Populations in Resource‐Constrained Environments

• Published in: Space Weather 2017-10, Vol.15 (10), p.1300-1313
• Main Authors: McCollough, J. P., Quinn, J. M., Starks, M. J., Johnston, W. R.
• Format: Article
• Language: English
• Subjects: Aerospace environments; Charged particles; Climatology; Data sampling; Design optimization; Environmental assessment; Environmental impact; Fluxes; Geomagnetism; Magnetospheres; magnetospheric plasma; measurement; Oversampling; Phenomenology; Real time operation; Sampling; Sampling methods; Satellite design; Satellites; solar energetic protons; Spacecraft; Spatial distribution; Telemetry; Temporal variability; trapped electrons; trapped protons
• ISSN: 1542-7390; 1539-4964; 1542-7390
• DOI: 10.1002/2017SW001629

Sampling of anomaly‐causing space environment drivers is necessary for both real‐time operations and satellite design efforts, and optimizing measurement sampling helps minimize resource demands. Relating these measurements to spacecraft anomalies requires the ability to resolve spatial and temporal variability in the energetic charged particle hazard of interest. Here we describe a method for sampling particle fluxes informed by magnetospheric phenomenology so that, along a given trajectory, the variations from both temporal dynamics and spatial structure are adequately captured while minimizing oversampling. We describe the coordinates, sampling method, and specific regions and parameters employed. We compare resulting sampling cadences with data from spacecraft spanning the regions of interest during a geomagnetically active period, showing that the algorithm retains the gross features necessary to characterize environmental impacts on space systems in diverse orbital regimes while greatly reducing the amount of sampling required. This enables sufficient environmental specification within a resource‐constrained context, such as limited telemetry bandwidth, processing requirements, and timeliness. Key Points Real‐time assessment of the space environment is streamlined by tailoring data sampling with an understanding of space hazard climatology With proper approximations, magnetic coordinates are appropriate for determining sampling cadence The eccentric dipole frame is suitable given dynamical, climatological, and resource considerations