A fast bow shock location predictor-estimator from 2D and 3D analytical models: Application to Mars and the MAVEN mission
C. Simon Wedlund, M. Volwerk, A. Beth, C. Mazelle, C. M\"ostl, J., Halekas, J. Gruesbeck, D. Rojas-Castillo

TL;DR
This paper introduces fast algorithms for predicting the bow shock location around planets using analytical models, validated on Mars data from the MAVEN mission, enabling quick and accurate shock crossing estimations.
Contribution
The paper develops new predictor-corrector algorithms for bow shock location estimation from spacecraft data, applicable across planetary environments, with demonstrated accuracy on Mars using MAVEN data.
Findings
Predicted shock position within 0.15 Rₚ of actual crossing
Refined estimate within 0.05 Rₚ using predictor-corrector method
Detected 14,929 bow shock crossings from 2014 to 2021
Abstract
We present fast algorithms to automatically estimate the statistical position of the bow shock from spacecraft data, using existing analytical two-dimensional (2D) and three-dimensional (3D) models of the shock surface. We derive expressions of the standoff distances in 2D and 3D and of the normal to the bow shock at any given point on it. Two simple bow shock detection algorithms are constructed, one solely based on a geometrical predictor from existing models, the other using this predicted position to further refine it with the help of magnetometer data, an instrument flown on many planetary missions. Both empirical techniques are applicable to any planetary environment with a defined shock structure. Applied to the Martian environment and the NASA/MAVEN mission, the predicted shock position is on average within 0.15 planetary radius of the bow shock crossing. Using the…
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