Abstract
As space‐based charged particle measurement pushes the technical envelope, resolution, both spatially and temporally, is ever improving. As such, the knowledge of the associated error must also improve. We present a method for correlating data collected from multiple sensors at different times in order to estimate the pointing error of each sensor. The method is demonstrated using flight data from the Dual Ion Spectrometer suite, part of the Fast Plasma Investigation on the NASA's Magnetospheric Multiscale mission. By looking at signals with sharp features in the direction of spacecraft spin, the relative error in look direction between sensors can be estimated with sub‐degree precision, roughly 20 times better than the native resolution in the azimuthal (spin) direction. These sharp features appear in nature often enough that a sufficiently large sample size can be identified, using an automated filter of routine science data, to calibrate the system, or post correct measured data. The relative pointing error can then be trended over time to monitor the evolution/aging of the measurement system. These data inform calibration/correction methods, should the error grow to a point where science quality is adversely affected.
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