The formation algorithm of errors models for satellite navigation systems and correction algorithm for aircraft navigation systems

Abstract

An aircraft navigation complex as a part of an inertial navigation system, a satellite navigation system and an adaptive nonlinear Kalman filter is considered. In the Kalman filter, when the estimation process diverges, the model is constructed using an evolutionary algorithm. The used divergence indicators analyze the measured signals; the directly unmeasured state variables are not examined. A divergence criterion of directly unmeasured state variables is proposed on the grounds of the reduced measurements and the variances of the reduced measurement noises. The algorithm modification effectiveness is demonstrated by using the flight experiment data. Keywords navigation complex, adaptive nonlinear Kalman filter, divergence indicator, reduced measurements, flight experiment data