Research On INS/CNS/Beidou Multi-source Navigation Method For Near Space Hypervelocity Vehicle

Near space is an important transition area for integrated operation of sea,land,air and space in future.Near space high speed aircraft with long range precision strike capability will be the core force in the future battlefield.Navigation system is an important subsystem of near space high speed aircraft,and it is an important guarantee to maintain the precision strike capability of aircraft.In recent years,with the improvement of China’s comprehensive national strength and scientific research ability,there are higher requirements for the accuracy and reliability of the navigation system of near space high speed aircraft.At the same time,the third generation Beidou satellite navigation system has completed the global networking,satellite navigation technology will no longer be limited by foreign countries,and Beidou navigation system will be further applied to the navigation system of near space high speed aircraft.Based on the above analysis,this paper focuses on the improvement of INS(Inertial Navigation System),CNS(Celestial Navigation System)and Beidou navigation systems in high-speed and dynamic environment,the main research work is as follows:Firstly,the CNS/INS dynamic deep integrated navigation method is studied in near space environment.In the dynamic environment,the spacecraft attitude maneuver will cause the star image to be trailing.Using the angular velocity information measured by inertial devices,an image restoration method is designed,which can effectively improve the success rate of star extraction.Due to the bad flight environment in near space,a CNS/ INS deep integrated navigation method is proposed to solve the problem of insufficient navigation stars.In the deep integration mode,the star sensor only outputs gray-scale image,the gray-scale error function is constructed with the aid of INS,the attitude misalignment angle is calculated by using nonlinear optimization method,and the misalignment angle is measured for filtering estimation.In the deep integration mode,there is no need for star pattern recognition,so it has higher computational efficiency than the traditional method.At the same time,it can still work when the number of navigation stars is only two,which improves the adaptability of the navigation system to extreme conditions.A star imaging error model based on second-order Markov process is proposed to solve the problem of star disturbance caused by aero optical effect.On this basis,a second-order state augmented H-infinity filtering method is designed,which can effectively improve the attitude accuracy in disturbed environment.Secondly,the Beidou/INS dynamic deep integrated navigation method is studied in near space environment.In the process of high-speed flight,the plasma sheath around the aircraft will affect the propagation of satellite navigation electromagnetic wave signal and cause the flicker of signal carrier phase.A scintillation noise model is used to simulate the influence of plasma sheath on signal propagation.Based on this,a robust tracking loop for satellite signal is designed.The robust filtering algorithm is used to replace the traditional phase-locked loop,which can suppress the influence of scintillation noise and effectively overcome the problem that the tracking accuracy of traditional PLL decreases under the condition of non Gaussian noise.Compared with other combination modes,Beidou/INS deep combination mode has better dynamic performance.An improved adaptive filtering algorithm is added based on the deep combination mode.According to the satellite altitude angle information of each channel,an adaptive fading factor is designed to adjust the weight proportion of measurement information,which can effectively improve the position accuracy.The effectiveness of the proposed method is verified by the measured data,and a virtual simulation scene is built to simulate the flight environment of near space high speed aircraft.The simulation results show that the proposed method has higher navigation accuracy and stronger robust adaptability.At last,the problem of multi-sensor navigation information fusion is studied.In order to further improve the position estimation accuracy,the star angular distance positioning information is introduced,and a multi-sensor federated filtering model is designed.Aiming at the time delay of different sensor data,a random multi-step delay processing algorithm is designed under the federated filter framework,which can effectively improve the fusion accuracy of navigation information.A fault diagnosis method based on multiple decaying chi square detection is designed to deal with the sudden sensor faults that may occur in the flight process of aircraft.A fault tolerant and delay tolerant dual state multisource navigation system is proposed to solve the problem of deceptive jamming of pseudolite signals.The simulation scene is built on the basis of theoretical research,and the multi-source navigation system is verified by computer simulation.The simulation results show that the fault tolerant and delay tolerant dual state multi-source navigation system can adapt to multi-sensor random delay,sensor failure and pseudo satellite deception signals at the same time.Compared with the traditional information fusion method,it has higher accuracy,adaptability and fault tolerance.In summary,aiming at the problems of the navigation system of near space high speed vehicle,this paper starts from three aspects: CNS / INS integrated navigation subsystem,Beidou / INS integrated navigation subsystem and multi-source navigation information fusion.Firstly,it improves the high speed and high dynamic adaptability from each subsystem level,and then solves the different sensor information fusion problems from the information fusion level.It provides the method and scheme reference for the navigation system design of the near space hypervelocity vehicle in the future,which has a strong practical value in engineering.