Convolutional Bayesian Filtering: A Generalized Framework for Handling Model Mismatch in State Estimation

By conditioning on an additional event that stipulates an inequality constraint between the real and virtual states, the standard conditional probabilities in Bayesian filtering can be transformed into convolutional forms. This generalized framework allows for explicit consideration of model mismatch, leading to more robust state estimation algorithms.