The Research Of Vector Tracking Algorithm Of GNSS Receivers

As an important part of the receiver processing satellite signals and obtaining the positioning results,tracking performance optimization is essential for improving the overall efficiency of receivers and improving the positioning resolution speed and accuracy.However,due to the dynamic nature of the receiver and the occlusion of the receiver signal in the urban environment,the positioning and navigation performance of the receiver is greatly reduced.At the same time,the computational complexity of the vector tracking algorithm also affects its hardware implementation.Therefore,in order to improve the positioning accuracy of GNSS receivers and reduce the computational complexity of vector tracking,this paper has carried out research on vector tracking algorithms,mainly including the following two parts:(1)A neural network aided GPS/ Beidou dual system integrated navigation algorithm is proposed.The pre filter and navigation filter structure are first applied in the vector tracking loop,and the pre filter structure is used instead of the traditional discriminator structure.Secondly,the estimated value of the navigation filter is used to adjust the pre filter structure.Finally,the output of the navigation filter is used as the input of the neural network,and the online training of the neural network is carried out.It provides more accurate code phase and Doppler information for navigation calculation part..(2)Compressed sensing-aided vector tracking loop is proposed.In this method,the code phase,carrier frequency and carrier phase information extracted from the compressed samples of the signal,which no longer needs to reconstruct the original signal,and then the output from discriminators used as the input of the navigation Kalman filter,on the one hand,the Kalman filter is used to estimate signal parameters for all satellites,and user Position,Velocity,Time is given based on measurements from all satellites;on the other hand,the navigation Kalman filter sends control commands to each NCO,drives the tracking loop to generate the local signals.The experimental results show that the position and velocity accuracy of the proposed algorithm is improved compared to the traditional vector tracking loop.It is more adaptable to weak signals and high dynamic environment than the traditional vector tracking loop.And compared with the traditional vector tracking algorithm,the algorithm proposed in this paper reduces the computational complexity.