Deepening Research On Anti-Mainlobe Interference Technology Based On Blind Source Separation Algorithm

When the interference signal falls within the main lobe of the radar signal,the main lobe cancellation method of the antenna array and the difference beam often requires the radar main beam to be aligned with the target;Applying adaptive beamforming to the main lobe interference will cause the main beam distortion of the peak shift of the sidelobe level to increase,which leads to an increase in the false alarm probability of the radar;The adaptive beam main lobe cancellation algorithm based on blocking preprocessing can solve the main lobe distortion,but also brings about the problem that the calculation amount increases the signal to noise ratio.The use of array antennas in the polarization domain through polarization matching can not completely eliminate the main lobe interference signal and the filtering effect of polarization matching will decrease rapidly with the increase of the polarization state error.In this thesis,we use the blind source to separate the main lobe interference of the anti-radar in the absence of the prior knowledge of the source signal and the channel parameters.This kind of algorithm can recover the unknown source signal by simply observing the signal according to the statistical characteristics of the input source signal.Individual independent components.For the blind separation of the radar signal,the target echo signal can be separated from the observed mixed signal of the radar array,the radar clutter and the enemy interference signal can achieve the effect of clutter suppression,and the target echo signal can detect the pitch of the target.Effective information such as azimuth,distance,speed,etc.,the interference signal can analyze the interference strategy pattern used by the enemy,so that we can choose better anti-interference measures.The radar clutter sometimes contains some useful information such as meteorological clutter.Aiming at the main lobe interference,this thesis studies the blind source separation algorithm based on fast fixed independent component analysis algorithm and matrix joint diagonalization feature vector.By establishing radar array signal model,the number of sources is pre-estimated and the characteristics of the received signal are analyzed.Analyze and determine the applicability of the blind source separation algorithm to the array signal model.Then the preprocessing of the observed signal includes de-equalization to eliminate DC coupling and pre-whitening processing,and then use the blind source separation algorithm based on different objective functions to process the separation matrix.Finally,the target echo signal is separated by peak detection according to the pulse compression principle.Signal and radar clutter.The algorithm performance indicators based on different signal-to-noise ratios and different objective functions include the correlation coefficient between the separated signal and the source signal,the peak signal-to-noise ratio,and the operation time and number of iterations of the separation algorithm.Through comparative analysis,it can be seen that both algorithms have better anti-interference performance.The JADE blind source separation algorithm has more effective suppression of main lobe interference than the Fast ICA algorithm,but the computation time is increased due to the increase of algorithm complexity.The number of iterations is not as good as the Fast ICA algorithm.The two algorithms do not greatly suppress the target echo signal and improve the output signal-to-noise ratio of the system.The higher the signal-to-noise ratio,the better the performance of the blind source separation algorithm.The performance of the dry-signal comparison algorithm is not obvious.As long as the signal-to-noise ratio is maintained,the algorithm can effectively separate the target echo signals.The simulation comparison algorithm for the direction of arrival is that the MUSIC algorithm is more accurate than the ESPRIT algorithm,but the calculation time is longer.The comparison is based on different SNR array elements and the incident angle of the incoming wave.The influence of the root mean square error is that the more the signal-to-noise ratio increases,the more the estimated performance is better.