Research On Satellite Spatial Interference Suppression And Mainlobe Conformal Technology

With the rapid development of satellite communications,how to improve the antiinterference ability of satellite communications has been widely concerned by many scholars.The spatial interference suppression technology based on array antennas has also been greatly developed.The basic idea of spatial interference suppression technology is to adaptively set weight coefficients for the antenna elements in the array according to the environment in which the array receives signals,so that the desired signal is within the main lobe region of the array pattern.While ensuring the desired signal directional gain,the interference signal direction is located at the null position of the pattern,realizing interference suppression.According to the idea of spatial interference suppression,DOA estimation and adaptive beamforming technology can be combined to achieve highperformance spatial interference suppression.Therefore,accurate estimation of the direction of interference signals and adaptive interference zeroing based on the estimated direction are key technologies for achieving spatial interference suppression.Based on this,according to the needs of practical application scenarios,this thesis conducts research from three aspects: DOA estimation for virtual subarray division,null broadening,and conformal main lobe technology.In terms of DOA estimation based on virtual subarrays,the classical spatial spectral estimation techniques provide a solid theoretical foundation.Null broadening and main lobe of the beam shape preservation are prominent issues in the process of interference suppression.By combining DOA estimation technology and classic Capon beamforming algorithms,and expanding and extending them on this basis,two-dimensional broadening of nulls and two-dimensional main lobe shape preservation can be achieved.A comparative analysis was conducted on DOA estimation techniques based on virtual subarray partitioning for large-scale arrays.Explored the DOA estimation performance of virtual linear arrays and virtual planar arrays,and analyzed the DOA estimation performance based on virtual subarray partitioning and undivided molecular arrays from two aspects: root mean square error and successful resolution,providing a certain reference for subsequent real subarray level signal processing.Considering the error of interference source direction estimation,the null broadening technique is considered.Expanding the idea of one-dimensional null broadening to twodimensional arrays,a two-dimensional null broadening technique based on increasing the direction of virtual interference sources is proposed.A null broadening algorithm based on interference source steering vector U-V domain extension is proposed to address the angle coupling problem in two-dimensional conization matrix calculation.Finally,a twodimensional null broadening algorithm based on interference space constraints was proposed by combining subspace ideas.Through simulation verification and comparative analysis,the performance of three algorithms for two-dimensional broadening of the null position was analyzed.In response to the problem of main lobe distortion in the adaptive interference zeroing process,the reasons for main lobe distortion in the Capon algorithm were first analyzed.At the same time,the one-dimensional main lobe conformal algorithm was extended to the two-dimensional array,and a two-dimensional main lobe conformal algorithm based on diagonal loading was proposed.Based on different signal SNR environments and the idea of feature space,a two-dimensional main lobe shape preserving algorithm based on feature space is proposed under the generalized sidelobe cancellation structure.Finally,a main lobe shape preserving algorithm based on main lobe subspace constraints is proposed by combining diagonal loading and feature space.The performance of three algorithms for two-dimensional shape preservation of the beam main lobe was verified and analyzed through simulation.