Research On The Acquisition And Tracking Algorithm Of Hypersonic Aerocraft Beidou Signal

When hypersonic aerocraft reenters the Earth’s atmosphere, the plasma sheath will be generated by its collision with ambient air. The plasma induced can potentially degrade Beidou navigation signals through amplitude attenuation and phase shift which vastly disturb the aerocraft’s reentry communication, even produced the blackout. Thus traditional acquisition and tracking methods must be modified in order to improve the performance of Beidou receiver.First, a nonuniform plasma sheath model is built for the purpose of studying the transmission properties of Beidou navigation signals in plasma sheath. The characteristics of received Beidou signals are discussed theoretically and experimentally in this thesis.Secondly, the influence of Doppler shift and Neumann-Hoffman code plus plasma sheath on the acquisition and tracking of Beidou signal is mainly discussed. Differential coherent accumulation algorithm could overcome the influence of navigation data bit transition and improve the acquisition sensitivity compared with traditional acquisition methods. This thesis also proposes utilization of maximum likelihood estimation in the FFT domain to find and estimate the Doppler shift at the same time to reduce the acquisition complexity. Extended Kalman filter based algorithm can track high dynamic and weak signal with low complexity when given the noise statistical characteristics. An adaptive extended Kalman filter algorithm based on Sage-Husa time varying noise estimator is applied to track hypersonic aerocraft received Beidou signals. Simulation results show that adaptive extended Kalman filter algorithm can maintain high tracking accuracy and sensitivity.Finally, the Beidou positioning algorithm is studied and the effect of plasma on hypersonic aerocraft’s positioning is analyzed. Further more, motion parameters of hypersonic aerocraft are achieved through least-squre method and Kalman filter algorithm. Simulation results indicate that Kalman filter algorithm has high positioning precision and convergent rate compared with least-squre method.