Research On Anti-jamming Technology Of High Dynamic GNSS Based On Spatial Domain And Sparse Domain

Global Satellite Navigation System(GNSS)has been widely used in military construction and daily life.Especially in the field of military guided weapons,due to the increasingly complex space electromagnetic environment,the satellite navigation signal itself is very fragile,and the requirement for anti-jamming technology of GNSS is getting higher and higher.Especially in the high dynamic condition,the state of the navigation receiver platform is extremely unstable,which shows that the direction of interference changes rapidly,and all the spatial anti-jamming means depending on the static state are invalid.Therefore,the anti-jamming problem of GNSS under the high dynamic condition has attracted great attention.This paper mainly studies the anti-jamming technology of high dynamic GNSS from two aspects of spatial domain and sparse domain,and resolves the problem of DOA mismatch and undersampling estimation in high dynamic environment respectively.Firstly,according to the motion characteristics of GNSS receiver carrier under high dynamic conditions,a signal statistical model under high dynamic conditions is established,and the applicability of disturbance signal obeying Gauss distribution is expounded.The G-NW algorithm is deduced,and the anti-interference performance of the algorithm is compared with the traditional power inversion algorithm.The results show that G-NW algorithm can effectively expand the nulling of received interference beams,to a certain extent,solve the problem of slow update of the weight calculation of received array signals in spatial domain,and ensure that the interference signal will not move out of the nulling under high dynamic conditions.The simulation results show that the anti-jamming performance of G-NW algorithm is better than that of power inversion algorithm.Secondly,in order to solve the problem that the G-NW algorithm widens the nulling and shallows the depth at the same time,a nulling widening and deepening algorithm based on Gauss statistical distribution(G-NWD)is proposed in this paper.The algorithm preprocesses the data by projection transformation method,extracts the interferencecomponent from the sampled signal,enhances the interference component by coefficient weighting,constructs a new covariance matrix on the basis of G-NW algorithm,and finally uses power inversion algorithm to complete interference suppression,so as to widen and deepen the nulling.Through simulation,the influence of disturbance parameters,deepening parameters and angle calculation deviation,power intensity change and snapshot number on disturbance suppression performance is analyzed.The simulation results show that under high dynamic conditions,G-NWD algorithm achieves depth increase on the basis of nulling widening algorithm,and improves the robustness of nulling widening anti-jamming algorithm.Finally,the problem of under-sampling under high dynamic conditions is studied.Aiming at the problem that more snapshots can not be obtained under high dynamic conditions,a fast compressive sensing method based on Bayesian theory is proposed,which uses the sparse characteristics of spatial signals and the Bayesian compressed sensing theory to solve the posterior mean and variance by estimating the super-parameters.Only the single snapshot data is used to reconstruct the interference of signal estimation.The simulation results show that the proposed algorithm not only improves the accuracy and success of DOA estimation at low SNR,but also reduces the running time of the algorithm,speeds up the convergence speed of the algorithm,and meets the anti-jamming requirements of high dynamic GNSS under under under-sampling conditions.