Research On Self-interference Cancellation Technology In LEO Navigation Augmentation System

Global Navigation Satellite System(GNSS)is a real-time navigation and positioning system that provides users with speed,time,and three-dimensional coordinates data.As a key infrastructure for obtaining spatial information,GNSS has significant military and civil value in defense,transportation,and other fields.However,the positioning accuracy of GNSS can only reach the meter level,and it is difficult to play an actual role in highprecision fields such as autonomous driving and smart agriculture that rely entirely on the GNSS.Therefore,researchers have proposed using low earth orbit satellites to enhance satellite navigation signals for high-precision positioning.When the low earth orbit navigation augmentation system realizes high-precision positioning,the navigation augmentation signal and the normal received signal of the low earth orbit navigation augmentation load will produce self-interference.To solve this problem,the current academic community mainly adopts self-interference cancellation technology to eliminate self-interference.The self-interference cancellation techniques are mainly divided into three types: spatial domain,analog domain and digital domain.This thesis mainly focuses on how to accurately estimate the angle information of the received signal in the spatial domain,and then achieve self-interference suppression.And how to ensure faster convergence speed and larger interference cancellation ratio in the digital domain.The specific research work is as follows.(1)For the problems of inaccurate estimation of the angle information of the received signal and poor interference cancellation ability in spatial self-interference cancellation algorithms based on adaptive beamforming,a spatial self-interference cancellation algorithm based on a combination of weighted improved multiple signal classification and LCMV is proposed.First,a new covariance matrix is obtained by reconstructing the covariance matrix of the received data.The corresponding noise subspace is constructed by decomposing the new covariance matrix with singular value decomposition.Then,the weighted value is built using the eigenvalue,and the direction of arrival estimation of the received signal is realized.Finally,LCMV adaptive beamforming algorithm is used to form null at the self-interference signal direction and gain at the interest signal direction.(2)For the problem of mutual restriction between convergence speed and interference cancellation ratio in digital domain self-interference cancellation schemes based on adaptive filter,an improved iterative variable step-size least mean square digital domain selfinterference cancellation algorithm is proposed.Firstly,a larger step factor is set in the initial stage to improve the convergence speed,and the nonlinear relationship between the step factor and the number of iterations is established based on the Versoria function.At the same time,the autocorrelation between the current error signal and the previous error signal is used to control collaboratively step factor.Then,the estimated self-interference channel impulse response is obtained by using the step factor,transmission signal and error signal.And the self-interference signal is reconstructed according to the known transmission signal.Finally,the reconstructed self-interference signal is removed from the received signal to achieve self-interference cancellation in the digital domain.