Research On GNSS/INS Deep Combined Adaptive Filtering Technology In High Dynamic Environment

By combining the output of the receiver tracking loop correlator or the discriminator with the INS measurement information to integrated navigation filtering,correcting INS measurement error,and using the INS Doppler information aided GNSS receiver,the deep coupled can effectively improve the stability tracking and fast capture performance of satellite signals in high dynamic environment,improve the anti-jamming performance of system,effectively solve the contradiction between anti-jamming and dynamic tracking performance.In the GNSS/INS deep coupled system,the accuracy of GNSS receiver baseband signal tracking and the integrated navigation filtering accuracy directly determines the precision and even the overall performance of the deep coupled system.Aiming at this,the main objective of this paper is to design high-performance GNSS/INS deep coupled filtering algorithm to solve the robustness problem of the system under high dynamic time-varying noise.Based on the design and simulation of high performance GNSS/INS deep coupled filtering algorithm,the paper first constructs the GNSS/INS deep coupled simulation platform,laying the foundation of simulation,verification and optimization for the design of the deep coupled algorithm.Secondly,developing the following four tasks,including the study of the GNSS/INS deep coupled structure and mathematical model,doing adaptive research of classical nonlinear filtering algorithm in high dynamic GNSS/INS deep coupled system,designing and simulating the prefilter and integrated navigation filter in high dynamic GNSS/INS deep coupled system.This paper focuses on the design of prefilter algorithm and integrated navigation filter algorithm in high dynamic deep coupled.In order to solve the problem of system noise related to code/carrier noise correlation in high dynamic depth coupled prefilter model,a prefiltering algorithm based on identical transform is proposed.The simulation results show that the algorithm can reduce the tracking error about 60%in high dynamic.In addition,a hybrid UKF algorithm UTC-AUKF algorithm with adaptive noise estimator is designed for noisy time-varying problem of high dynamic system.The simulation results show that the UTC-AUKF algorithm can improve the navigation accuracy of one time and reduce the computation amount by about 10%compared with the conventional UKF algorithm when the noise of the high dynamic system is time-varying.