Research On Interference Suppression Algorithm Of Adaptive Beamformin

Adaptive beamforming technology,as a key technology in array signal processing,is widely used in various fields such as wireless communication systems and medical imaging.As the smart antenna system has higher beam gain than the omnidirectional antenna,the anti-interference capability of the adaptive beamforming algorithm is more stringent.There are many interference factors in the process of beamforming and adaptive filtering.To address the problem of mutual coupling between array elements due to small spacing,an adaptive beamforming algorithm based on matrix reconstruction under unknown mutual coupling information is studied to improve the beamforming ability at low signal-to-noise ratios.In addition,optimization was carried out to address the issue of inaccurate initial value estimation in the LMS algorithm,and an optimized LMS adaptive filter FPGA implementation was designed to verify its filtering effect.The main research content and achievements are as follows:(1)Learn a basic array antenna model;Derive the principles and criteria of beamforming;Analyze the classic adaptive beamforming algorithm and demonstrate its anti-interference ability through simulation.(2)An adaptive algorithm for matrix reconstruction was studied to address the issue of unknown mutual coupling information between array elements,and improved the algorithm.Reconstruct the covariance matrix containing mutual coupling information,and obtain stable beamforming through power sampling.In response to the problem of unsatisfactory beamforming performance under low signal-to-noise ratio,the new algorithm utilizes the characteristics of the mutual coupling matrix to assign an error value to the desired signal steering vector,thereby improving the stability of the steering vector.And simulation and comparison were conducted under different experimental conditions to prove that the improved algorithm has more robust anti-interference ability under low signal-to-noise ratio conditions.(3)Optimize the LMS adaptive filtering algorithm and validate it with FPGA.On the basis of the original algorithm,the estimated value of the cross correlation between the initial received data and the expected data is optimized at low snapshots to reduce initial errors.The simulation results show that the optimized LMS algorithm has stronger filtering ability against noise.Finally,in order to verify the feasibility of the filter,a FPGA adaptive filter design verification was carried out to optimize the LMS algorithm.Design modules in FPGA,model the overall system and write hardware language using software platforms such as Quartus II.Finally,verify through simulation results that the designed system has good signal filtering effect and has certain engineering application value.