Key Technology Study On Vector Receiver/Inertial Navigation Deep Integration System

With the rapid development of the technology,Position,Navigation and Timing(PNT)have been the fundamental information for modern society.Vehicle positioning,smartphone location,weapons guidance all reply on PNT information.A standalone Global Navigation Satellite System(GNSS)is not sufficient for the various demands.GNSS/Inertial Navigation System(INS)deep integration system is one of the most promising technologies,which have been a research hotspot in the community.GNSS/INS deep integration system performed better positioning accuracy,strong anti-interference capacity and dynamic tolerance.This research was carried out based on a National Natural Science Foundation of China and a key national defense research project,key problems of the vector tracking based GNSS/INS deep integration system were investigated,and they were summarized as following:(1)For solving problem of error propagation between channels,we analyzed the mechanism of Vector Tracking Loop(VTL),derived the errors propagation model and studied the errors characteristics;then,a channel fault detection method was designed;finally,a semi-physical experiment system was constructed for evaluating the performance of the proposed method,and the results demonstrated the effectiveness of the proposed method;(2)For the low-accuracy of the local frequency reference,a Chip Scale Atomic Clock(CSAC)was introduced for providing accurate frequency base,relationship between Dilution of Precision(DOP)and time errors was constructed;observability analysis was operated for the clock errors related states;a CSAC was integrated into an Intermediate Frequency(IF)collector,experiments were carried out for evaluating the system performance;the results showed that CSAC was able to improve the accuracy of the VTL,and the clock drift could be excluded from the new VTL model,which could reduce computation load of the navigation filter;(3)For the dramatically increasing computation load initialed by satellites amount,firstly,a measurement differential method was proposed to remove the clock bias and drift variables;then,a cascaded filter method was designed based on this;finally,a numeric simulation was conducted for evaluating the performance of the proposed method,results showed that the cascaded scheme could reduce the computation load with almost unchanged positioning accuracy.(4)For the non-linearity of the integration filter and abnormal noise,Unscented Kalman Filter(UKF)and Cubature Kalman Filter(CKF)were employed for nonlinear problem,and furtherly an Adaptive UKF(AUKF)and an adaptive Robust CKF(ARCKF)were designed for improving the accuracy under abnormal noise;numeric simulation results demonstrated the robustness of the proposed method.This thesis investigated the Vector/Inertial Navigation System Deep Integration System,the system robustness was enhanced by analyzing the channel errros propagation;the navigation solution was improved through employing the CSAC as the frequency base;a cascaded integration architecture was designed for reducing the computation load;nonlinear filters were utilized for alleviating the nonlinearlity on the navigation solutions accuracy.Basically,these four key technologies were benefitial for the system performance enhancement.