Research on the navigation method of high speed differential rotation guided ammunition with ballistic assistance prediction under GNSS denial

In complex environments such as high dynamics and weak signals, a satellite signal compensation method based on prefabricated trajectory assistance and an improved adaptive Kalman filter is proposed for a 155 mm differential rotating rear-body control-guided projectile to address the situation of satellite signal flickering and loss in projectile navigation systems due to environmental limitations. First, establish the system state and measurement equation when receiving satellite signals normally. Second, a seven-degree-of-freedom external ballistic model is constructed, and the ideal trajectory output from the ballistic model is used to provide the virtual motion state of the projectile, which is input into a filter as a substitute observation when satellite signals are lost. Finally, an adaptive Kalman filter (AKF) is designed, the proposed adaptive Kalman filter can accurately adjust the estimation error covariance matrix and Kalman gain in real-time based on information covariance mismatch. The simulation results show that compared to the classical Kalman filter, it can reduce the average positioning error by more than 38.21% in the case of short-term and full-range loss of satellite signals, providing a new idea for the integrated navigation of projectiles with incomplete information under the condition of satellite signal loss. • High-speed differential spin tail-guided projectile navigation: prefabricated trajectory aid under GNSS rejection. • Predict projectile virtual motion using ballistic error term, noise model & adaptive noise switching. • Use prefabricated trajectories as auxiliary observations for incomplete projectile navigation info when GNSS is rejected. • Adaptive Kalman filter architecture for projectiles: adjusts measurement noise via new covariance mismatch adaptation.