A Generalized Augmented Gaussian Approximation Filter for Nonlinear Systems with Non-additive Correlated Noises

Abstract

Considering that nonlinear systems exist non-additive correlated noises, a generalized augmented Gaussian approximation filter (GAGAF) is proposed. The proposed filter makes use of the state augmented method to overcome the limitation of traditional nonlinear filters based on additive correlated noises. Based on the proposed filter framework, a novel augmented cubature Kalman filter with non-additive correlated noises (NACKF) can be developed through utilizing the spherical-radial cubature rule to computer the multi-dimensional integrals approximately. Simulation results validate the efficiency and feasibility of the proposed filter.