Designing an error model for navigation sensors using the Bayesian approach

Abstract

The paper considers a problem of designing error models for navigation sensors the data of which are used in fusion algorithms. Within the Bayesian approach, an algorithm is proposed that allows not only estimation of model parameters, but also identification of its structure. As a result of solving the joint problem of hypotheses recognition and parameter estimation, a shaping filter describing sensor errors is designed. An example is given to illustrate the performance of the proposed algorithm.