Research On Multi-beam Anti-jamming Technology Based On Signal Cyclostationarity And FPGA Implementation

Adaptive beamforming technology is the core of array signal processing,it has been widely used.Because the spatial spectrum is different between the useful signal and the interference and noise signal,so the desired signal can be extracted.With the rapid development of communication technology,various intentional or unintentional electromagnetic interference is also increasing.In order to make the communication equipment can send and receive the useful signal in all kinds of environment,the development of effective anti-jamming technology has become the focus of this paper.In depth study of adaptive beamforming technology,this paper makes a detailed study on the two aspects of non blind and blind adaptive beamforming.Aiming at the problems of several typical non blind algorithms and blind algorithms,this paper presents an improved method.In this paper,the theory of adaptive beamforming and the cyclostationarity of signals are introduced.Based on these knowledge,the advantages and disadvantages of SMI algorithm,CAB algorithm and SCORE algorithm are analyzed in detail.In the practical application,the cyclic frequency error will cause the performance of the CAB algorithm to decline sharply or fail.In order to overcome this drawback,this paper proposes an adaptive forgetting factor cyclostationary beamforming algorithm.The algorithm can adjust the forgetting factor adaptively according to the change of the surrounding environment,and correct the error of the cyclic autocorrelation matrix.Thus the optimal weight is obtained,and the maximum SINR is output and a good beam pattern is formed.The improved algorithm proposed in this paper can effectively improve the performance of the other improved algorithm when the cycle frequency error is large.The simulation results under different parameters show the practicability and effectiveness of the improved algorithm.In order to solve the problem of cyclic frequency error,this paper proposes a another method to solve the problem by using swarm intelligence optimization algorithm,which is fireworks algorithm based on the explosion search to optimize the CAB algorithm.The basic principle of fireworks algorithm is introduced in detail in this paper.With the help of the global optimization ability of the fireworks algorithm,it can effectively solve the influence ofthe cyclic frequency error on the performance of the CAB algorithm.The simulation results show the practicability and effectiveness of the improved algorithm.In order to solve the problem that the traditional SMI algorithm is easy to be distorted and difficult to be applied in engineering practice,this paper propose a genetic matrix adjoint inversion algorithm.The detailed theory of the improved algorithm is derived,and then it is verified by computer simulation.Then the system composition and the concrete implementation scheme of FPGA are introduced in detail.And according to the given performance indicators of the system modules to debug,the feasibility and reliability of the genetic matrix adjoint invert algorithm is verified.Finally,according to the test conditions,the system structure is optimized and improved,and the FPGA implementation of the algorithm is applied to the Beidou satellite navigation anti-jamming system.The simulation and practical application show that the improved algorithm is very practical.