In-motion alignment adaptive filter method for GNSS-aided strap-down inertial navigation system

In view of the rapid-launch requirement for vehicle weapon system, an in-motion alignment adaptive filtering method for GNSS-aided strap-down inertial navigation system (SINS) is proposed. The in-motion transfer alignment is composed of two stage, i.e. coarse alignment and precise alignment. In the coarse alignment stage, the coarse acquisition of the SINS's attitude is accomplished by taking GNSS as the observation datum, which can reduce the effect of initial deviation uncertainty on the precise alignment stage. In the precise alignment stage, the horizontal and azimuth filters work in parallel to improve the attitude estimation accuracy using three-axis attitude decoupling in the process of vehicle system movement. Meanwhile, the covariance shaping process is introduced by taking the minimum Frobenius norm as the optimization index to realize the self-adaptive in-motion alignment Kalman filter and improve the robustness of the system. Numerical simulation shows that the double-filter parallel scheme with covariance shaping adaptive Kalman filtering can effectively solve such problems as poor stability and low alignment accuracy, and the alignment accuracies are increased to 1.5' (1σ, horizontal) and 6' (1σ, azimuth).