Development of a Bow-tie Inversion Technique for Real-time Processing of the GOES-R SEISS MPS-HI Electron Channels and Comparison with the Baseline Matrix Inversion Technique

The Space Environment In-Situ Suite (SEISS) on GOES-R includes a new instrument for measuring radiation belt electrons and protons, the Magnetospheric Particle Sensor – High Energy (MPS-HI). The baseline calibration algorithm for the conversion of raw MPS-HI electron telescope counts to fluxes is based on the inversion of the geometric factor matrix that relates raw counts to electron fluxes, C=R_ij F. This matrix is derived from the Geant4 simulation results of electron transport through the telescope solid state detectors, scaled and shifted based on measurements in electron beams. The inverse matrix, R^-1_ij, provides the electron fluxes from the measured counts and has no constraints placed on the inversion in order to ensure a realistic result. The baseline algorithm exhibits substantial errors in the electron flux determination, approaching or exceeding 100% in the high energy (E7-E10) differential channels and the integral E10A channel. Our first approach to mitigating the problem is to apply instead a diagonal array produced by the so-called bow-tie technique for the characterization of a particle sensor instrument response. The purpose of the bow-tie analysis is to calculate for each energy channel an energy/geometric factor pair applicable to a wide range of energy spectra, and for which the geometric factor error is minimized. Previous applications of the technique have used small analytical families of energy spectra. For the first time, to our knowledge, we derive bow-tie factors using a large number of observed high-resolution spectra. Specifically, we use the cross-calibrated CRRES satellite MEA and HEEF data set from the period 1990-1991 (Johnston et al., AFRL-RV-PS-TR-2014-0016, 2014), restricted to 6<L<8. A number of randomly selected CRRES spectra from a subset of the data is used to perform the bow-tie analysis and determine the channel energy/geometric factor characteristics. The remaining CRRES spectra are first converted to counts using the Geant4 simulation results, and then inverted back to fluxes using both the baseline matrix inversion and the bow-tie technique inversion. The retrieved electron spectra from the two methods are then compared to the original CRRES proxy spectra. We conduct both case study and statistical error analysis of the two inversion techniques to show that, in general, the diagonal bow-tie array performs better than the baseline matrix inversion for the high energy (E7-E10) differential channels and the integral E10A channel. We repeat our study for different bow-tie analysis samples and CRRES proxy data sets, and compare the results.