Research On Vector Tracking Technology Of GNSS Receiver

At present,the application based on location information is growing explosively.With the increasing demand for GNSS(Global Navigation Satellite System)services and the higher demand for the receiver performance,it is difficult for the traditional signal receiving method to meet the requirements of this trend.Compared with scalar tracking in the traditional receiver,vector tracking has stronger robustness in harsh environment.However,for vector tracking,the tracking accuracy of weak signal and the ability to bridge occluded signals need to be improved,and there are still some problems such as fault propagation,so it needs to be further improved.This thesis focuses on the above issues,the main work and innovative achievements are outlined as follows:1.Aiming at the problem that the output error of the discriminator in the vector tracking loop is large and the tracking accuracy is low in the weak signal environment,the prefilter based on the adaptive cubature Kalman filtering(CKF)algorithm is proposed to replace discriminator.By taking the advantage of CKF,which has high nonlinear filtering accuracy,the proposed method can directly process the I/Q data output from the correlator,and obtain the carrier frequency error and code phase error.Furthermore,using innovation to estimate the covariance of measurement noise adaptively makes CKF have better adaptability when the signal power changes.The experiment results show that the proposed method has higher tracking accuracy in the weak signal environment,and can obtain more accurate navigation solution.2.To solve the problem that vector tracking loses the ability of predicting satellite signal parameters when all GNSS signals are occluded,a robust GNSS signal tracking method based on adaptive motion constraint is proposed.During GNSS outage,motion constraints are used as virtual measurements to estimate the vehicle’s position and velocity after identifying the motion state,and the receiver clock error is estimated based on the improved prediction model,which is the combination of quadratic polynomial model and autoregressive model.As a result,the parameters of GNSS signals can be predicted in real time with the old ephemeris.Furthermore,in order to improve the prediction accuracy,this paper adopts fuzzy inference to adjust the detection threshold of motion state adaptively.Experimental results show that the method can not only provide continuous navigation service during the absence of GNSS signals,but also can quickly lock the recovered signal by using the predicted parameters without the need for reacquisition.In addition,to solve the problem that the data generated by the occluded satellite signals contaminate the navigation solution,an improved carrier noise ratio calculation method that dynamically adjusts the calculation time interval is used to detect the occluded signals,and the method of removing the abnormal receiving channels from the vector tracking loop is given.By adding the detection and isolation of the occluded signals,it is helpful to maintain a stable navigation output during the occlusion and improve the ability of bridging the recovered signals.3.In view of the lack of research on receiver autonomous integrity monitoring(RAIM)algorithm applied in vector receiver,the problems in the application of RAIM are analyzed from two aspects of fault detection and fault identification,and the fault diagnosis ability of RAIM algorithm applied in vector receiver and scalar receiver is compared.Experiment results show that the RAIM performance of vector receiver is lower than that of scalar receiver.In addition,to solve the problem of low fault identification rate caused by fault propagation in the vector tracking loop,this paper proposes to suppress the propagation of fault information by adopting the robust algorithm,and obtain the expansion factor of the robust algorithm based on convolutional neural network.Compared with the traditional robust algorithm,the proposed algorithm can effectively weaken the adverse influence of fault on navigation solution.Finally,the accuracy of fault identification is improved.4.In order to improve the signal tracking ability of GNSS receiver,a dual-loop fusion structure combining vector and scalar tracking loop is proposed.This structure uses the output of the two loops adaptively according to the carrier-to-noise ratio and dynamically use the frequency information of vector tracking loop to assist the scalar tracking loop under the control of carrier frequency error.The experiment results prove that the proposed structure has the advantages of both tracking modes,and the signal tracking ability is improved.