Overbounding Revisited:Toward a More Practical Approach for Error Modeling in Safety-Critical Applications

摘要

Overbounding navigation measurement error is essential to ensuring integrity for safety-of-life applications.Most existing overbounding methods rely on representing the actual measurement error distribution with a continuous probability distribution model(e.g.a Gaussian).A key limitation of these methods is validation using empirical data,since it is not immediately evident how to develop tests to establish the conservatism of a continuous distribution using a very large(and continuously growing) population of statistical samples.This problem is particularly acute in the distribution tails,where comparatively little statistical data is available.We propose a discretized overbounding methodology as a practical solution for safety validation.With a discrete overbound,it is possible to(1)define a clear and consistent set of empirical validation tests and to(2) introduce a distribution shape that directly accounts for uncertainty in modeling the distribution’s far tails.