Abstract: During the identification of instrument error of gimbal inertial navigation system vehicle test, there is a serious multicollinearity exit in this system because the input acceleration is small. Application of the conventional least squares method can bring some questions, such as the variance may be enlarged and the parameter estimated value unstable and so on. In this paper, the empirical Bayes ridge estimation is proposed in the instrument error identification of GINS vehicle test. The simulation results showed that compared with the conventional least squares method, the empirical Bayes ridge estimation can enhance the precision of the parameter identification and can overcome the influence of the multicollinearity.

Key words: GINS, Vehicle test, Empirical Bayes ridge estimation