A nonlinear attitude estimator with desirable convergence properties

Abstract

A nonlinear attitude estimator is considered in this paper. The estimator shares several properties with estimators previously considered including ease of implementation and guaranteed asymptotic stability. The proposed algorithm is based on Poisson's equation and propagates the attitude estimate using measurements taken by typical low-cost sensing systems. Rate gyro bias estimation is also considered. The estimator structure is derived using an alternate attitude error function, which results in desirable convergence properties. These properties are demonstrated in simulation where the proposed attitude estimator is shown to achieve a faster convergence rate than an attitude estimator considered in the literature.