Planetary flyby attitude estimation in an intense radiation background based on cauchy uncertainty

There are many estimation problems where both impulsive measurement and/or process noise occurs. Handling outliers in the data has been a heuristic process. Recently, a recursive estimator for linear systems with additive measurement and process uncertainties modeled as heavy-tailed Cauchy probability density functions has been developed. This new scheme directly handles impulsive noise. In fact, for Cauchy noise, this estimator produces the conditional mean and is thereby a minimum variance estimator. To demonstrate its performance relative to a Kalman filter, this new estimator is applied to a planetary flyby, where the star-tracker measurements are impulsive due to the electromagnetic radiation characteristics of the planet.