In order to solve the problems of Kalman filter dispersion and inability to accurately track the error changes in the vehicle combination navigation system， an improved adaptive filtering algorithm is designed. By analyzing the judging condition of filter divergence in principle， combining Sage-Husa filtering with multiple fading filtering algorithm， the fading factor is introduced in the filtering process. The filtering state and updating strategy are switched by the divergence condition， so that the state of filter returns to normal in time when divergence occurs. The improved algorithm is subjected to Jetlink inertial guidance/odometer combination navigation simulation tests and track of vehicle experiment. Simulation and experimental results are presented that the divergence of filter can be suppressed， and in the meanwhile， the adaptability and stability of the filter are enhanced to a certain extent.

To improve the tracking accuracy of the hypersonic gliding target in the near space, a novel maneuvering model is established based on the change rule of flight path angle. In order to estimate the position and velocity of the target in the radar measurement coordinate system, the angle of the target's trajectory profile is analyzed. Because of the similar change rule between the change rate of flight path angle and that of the inclination angle, it is proposed to use the inclination angle instead of the flight path angle for establishing the maneuvering model. The change rate of inclination angle is described as a zero mean sinusoidal autocorrelation stochastic process and a Markov model is established. The angular relationship is mapped to the positional dimension for establishing a spatial model. To make the system state model linear, the model is divided into the front-end angle sub-filter and the back-end position sub-filter, and the angle sub-filter drives the position sub-filter for tracking. The parameters of the model are set through simulation. The experimental results show that the model has better tracking accuracy.