Adaptive transfer alignment method based on the observability analysis for airborne pod strapdown inertial navigation system

For the airborne pod strapdown inertial navigation system, it is necessary to use the host aircraft's inertial navigation system for the transfer alignment as quickly and accurately as possible in the flight process of the aircraft. The purpose of this paper is to propose an adaptive transfer alignment method based on the observability analysis for the strapdown inertial navigation system, which is able to meet the practical need of maintaining the navigation accuracy of the airborne pod. The observability of each state variable is obtained by observability analysis of system state variables. According to the weight of the observability, a transfer alignment filter algorithm based on adaptive adjustment factor is constructed to reduce the influence of weak observability state variables on the whole filter, which can improve the estimation accuracy of transfer alignment. Simulations and experiment tests of the airborne pod and the master strapdown inertial navigation systems show that the adaptive transfer alignment method based on the observability analysis can overcome the shortage of the weak observability state variables, so as to improve the alignment and the navigation performance in practical applications, thus improving the adaptability of the airborne pod.

Automated summary

This paper proposes an adaptive transfer alignment method based on observability analysis to improve the navigation accuracy of airborne pods. By analyzing the observability of each state variable in the electronic system and using a transfer alignment filter algorithm with adaptive adjustment factor, the influence of weakly observable state variables on the entire filter is reduced, thus improving the estimation accuracy of transfer alignment.