Robust Adaptive Beamforming Of GPS Receiver

Global Position System(GPS)is widely adopted in military and civilian fields,for its all-time,all-weather characteristics.Since Satellite navigation receiver is exposed in increasingly complex environment,the received signals are very weak,and a variety of man-made interference signals are accompanied,GPS is susceptible to a variety of interferences.In order to ensure the normal work of the GPS receiver,eliminate the effects of the spatial interference and increase the rate of signal to interference plus noise(SINR)of the ouput,we study the robust beamforming for the GPS receiver in this thesis.The main study in this paper are as follows.Firstly,the basic principle and processing model of array signal and the basic rules of optimal statistical beamforming are introduced.In addition,robust adaptive beamforming algorithms,such as generalized diagonal-loading adaptive beamforming algorithm,eigen-subspace adaptive beamforming algorithm,and blind beamforming algorithm are proposed to improve the performance of signal processing model.Secondly,the robust beamforming algorithm based on sidelobe canceller is introduced,and the working principle of the generalized sidelobe canceller is analyzed.The common construction method of blocking matrix is analyzed,and the blocking matrix can be formed accurately in the desired signal direction.The algorithm will fail when the angle mismatch is reached.Facing to the above problem,this paper presents the method that the blocking matrix and the weights of the lower branch are combined into one parameter,while the blocking parameter are introduced,and the errors of the covariance matrix are taken into account.The error parameters are given by the performance of the beamforming algorithm and the constraint equation is given by the worst performance beamforming algorithm.So,the blocking degree of the blocking matrix and the influence of the introduced parameters on the beamformer are simulated.Then,the influence of steering vector mismatch based on several algorithms caused by array error is analyzed.Aiming at the limitation that the SQP steering vector correction algorithm is easy to converge to the direction of the interference angle,the constraint condition in the algorithm is improved,and the constraint term is obtained by increasing the convergence angle of the signal angle in the ideal signal angle region.In order to solve the problem of dynamic source in real time,the subspace trajectory tracking algorithm in spatial spectrum estimation is proposed to give the signal subspace,and then the noise is obtained by solving the noise subspace in the subspace projection algorithm.According to simulation,weanalysis the output performance of the algorithm in dynamic perturbation.Finally,the covariance matrix of the interference and noise containing the expected signal is analyzed,which leads to the cancellation of the signal,and is needed to restructure the covariance matrix,and that introduces several common covariance matrices.For the problem that the angle range of the Capon spectrum is integrated,the angle range of the signal is too large,and the integral range is reduced.The paper put forward the covariance matrix that is reconstructed by integrating the interference angle range.In order to solve the problem of severe attenuation of most algorithms in the case of high signal-to-noise ratio(SNR),we propose a covariance matrix to obtain the eigenvalue decomposition by the maximum likelihood method,and then rearrank the signal power,taking into account the steering vector mismatch problem.Simulation results show that the covariance matrix of this algorithm has a high degree of fit with the ideal covariance matrix,and the output SINR works well and has a fast convergence speed under smaller snapshots.