Spectral redshift observation-based SINS/SRS/CNS integration with an adaptive fault-tolerant cubature Kalman filter

Abstract

This paper develops an enhanced fault-tolerant strap-down inertial navigation (SINS)/spectral redshift navigation (SRS)/celestial navigation (CNS) integration system. In the developed system, a new SRS observation equation based on Doppler shift is established to improve the accuracy and anti-interference performance of SINS/SRS/CNS integration. Subsequently, an adaptive fault-tolerant cubature Kalman filter (AFTCKF) is proposed to inhibit the effect of noise uncertainty and outliers in observations on state estimation. The AFTCKF promotes the robustness of the cubature Kalman filter, in which the maximum likelihood method is adopted for the online estimation of observation noise statistics, and the sequential probability ratio test and the chi-square test are employed in the determination of Kalman gain to further resist the outliers in the filtering procedure. The developed SINS/SRS/CNS integration system not only has the capability to maintain the stability of the navigation system in high-dynamic circumstances, but also is robust against the observation uncertainty. Simulations and comprehensive analysis have been conducted to verify the effectiveness of developed SINS/SRS/CNS integration.