The Optimization On Suppression Interference Algorithms For HF Surface Wave Radar

The High Frequency Surface Wave Radar (HFSWR) which can detect targets over the horizon by using vertically polarized waves along the sea diffraction theory. It works in the complex electromagnetic environment, and causes a lot of strong external noise and disturb.Shock interference is a typical strong interference, occurs in high frequency, in short time but strong power and so on. It can raise the noise floor heavily in Doppler, and the detection performance of target peak is depressed. The ionosphere interference is made of transmitted signal which is reflected. It difficult to distinguish and eliminate because the clutter is similar with the originals in frequency domain. So it's necessary to study the ways to suppress interference for The High Frequency Surface Wave Radar.The thesis aims at proposing a optimization method on suppressing interference. The aim at improving HFSWR's resistance to external interference, and then to improve the target detection's ability. The thesis studies two aspects: the better methods on suppressing both burst interference and ionosphere interference.In research on suppressing burst interference,normally algorithmic process is locating the interference range firstly, then interval date to zero and the data reconstruction by the right data nearby the interference range lastly. The paper summarizes the advantages and disadvantages of the traditional interference detection algorithms: wavelet transform algorithm and matrix decomposition algorithm, and then applies the algorithm combining wavelet transform and matrix decomposition in order to improve accuracy about interference range. According to the different types of burst interference,two ways of data recovery program proposed in data reconstruction, both AR prediction model and RBF neural network algorithm. The simulation results show that the total program after optimization can suppress three different types of interference, on the base of reducing the noise floor in the Doppler domain,and improve HF radar's impact interference suppression's abilities greatly.In research on suppressing ionosphere interference,normally algorithmic process is increasing the transmission frequency on radar, in order to make the signals penetrate the ionosphere, not reflected back to the receiver which caused the interference and make bad performance on radar system. But high frequency will reduce the ability to detect the further object. Therefore, this paper uses the Kalman filter weighted fusion algorithm to mixture data with electromagnetic environment spectral information on HFSWR. Then select the best work of the band by the average power using the optimized minimum criteria. This program can guarantee both the long-range radar detection capability, and suppress the ionosphere interference in maximum extent.