Analysis And Suppression Of Ionospheric Clutter Based On Received Signals From Array Antennas

High-frequency surface wave radar array antenna has been vigorously developed in the field of marine environment monitoring in the past four decades by virtue of its advantages of ultra-visible range,wide range and all-weather real-time monitoring.In practical applications,the ideal zero trap cannot be formed at the top of the array antenna,which makes the radar waves enter the radar receiver from the top by ionospheric reflection and form ionospheric clutter in the return spectrum,resulting in unusable metaecho data at specific distances,which seriously limits the detection performance of the array antenna.Therefore,the research on the suppression of ionospheric clutter in array antennas is of great significance to the development of array antennas.In this paper,on the basis of multi-domain analysis of clutter characteristics,the traditional orthogonal projection filtering algorithm is studied in depth,and the problems of the traditional method are analyzed by processing simulated data and real measurement data,and improvement methods are proposed.VMD is introduced to separate the signals of the target presence frequency to improve the accuracy of clutter covariance matrix construction.The signal in the RD domain is converted to the time-frequency domain by GST processing,so that the clutter suppression no longer depends on the adjacent distance element echo information.The effectiveness and superiority of the proposed algorithm are then verified by processing the simulated data and the measured data.The main research and innovation points of this paper are as follows.1)Combined with the special application background of marine environment monitoring,new clutter suppression evaluation indexes are added.The extraction errors of the firstorder peak position and echo intensity,which are closely related to the sea surface state,are added on the basis of the improved signal-to-noise ratio of the traditional first-order spectral region.And the scientificity and necessity of the new indexes are illustrated by processing the simulated data and the measured data through the traditional algorithm.2)The VMD algorithm is introduced to combine the characteristics of the cluttercontaining signal and determine the K value by the reciprocal number.The accuracy of the clutter covariance matrix is improved because VMD separates the signal with the target presence frequency and then denoises the separated signal.By processing the simulated data and the measured data,it is illustrated that the proposed method effectively reduces the echo intensity extraction error.3)The CM-GST algorithm is proposed to compensate the shortcomings of traditional time-frequency analysis and improve the time-frequency resolution of data.Later,the spurious suppression methods based on time-frequency filtering and component-based time-frequency correlation are proposed in the time-frequency domain,respectively.The two methods are processed separately for simulated and measured data,and compared with the traditional methods to verify the effectiveness of the algorithms.