Study On Robust Adaptive Anti-Jamming Method

With the advancement of technology and the rapid development of electronic countermeasures,the electromagnetic environment has become increasingly complex,which puts higher requirements on the interference suppression performance of radar system.On the one hand,nonstationary interference can largely degrade the anti-jamming performance of traditional algorithms.On the other hand,radar is often affected by strong clutter in practical engineering applications.In this circumstance,it is difficult to obtain effective interference learning samples,which can affect interference suppression performance.Therefore,improving the robustness of radar anti-jamming technique is an important topic,this thesis mainly focuses on the study of robust interference suppression algorithm.The beamforming technology is an effective spatial domain anti-jamming method,and the adaptive beamforming technology can adaptively adjust the weight vector according to the change of the external interference environment,thereby achieving the purpose of suppressing interference.In this thesis,a typical application of adaptive beamformer??adaptive sidelobe canceller is analyzed in detail,and the main factors affecting its performance are studied.Due to the motion of the interference or the radar platform,the interference signal will be nonstationary.In this circumstance,the conventional anti-jamming algorithm is difficult to provide sufficient degrees of freedom to suppress such nonstationary interference.Aiming at this problem,this thesis mainly studies the methods of covariance matrix taper,snapshot perturbation and beam space sidelobe cancellation,which can adaptively broaden the null of pattern.Then the similarities and differences of these methods and their anti-jamming performance under different conditions are analyzed.Simulation results demonstrate that compared with the conventional anti-jamming algorithm,the null broadening algorithm can effectively solve the interference suppression ability degrading problem caused by the weight mismatch of the conventional adaptive processing method.Under multi-pulse conditions,the radar's anti-jamming ability is greatly affected by clutter.Strong background clutter will not only annihilate the interference signal,but also consume many degrees of freedom of adaptive processing,making the traditional anti-jamming algorithm invalid.Motivated by this,the interference suppression method based on time domain constraints under multi-pulse conditions is employed in this thesis.The specific idea is to suppress clutter by sliding window cancellation method firstly,and then obtain effective interference samples for weight training,and finally adopt the sidelobe cancellation method to suppression interference.In order to improve the update rate of adaptive weights,the method of segment sidelobe cancellation is performed,but the weights of different segments will increase the random phase modulation of the clutter,resulting in the broadening of the clutter spectrum.Considering this problem,this thesis takes the output of the zero Doppler filter as the constraint object,and adopts a method that can avoid the spread of the clutter spectrum and effectively suppress the interference.Simulation results show that the adopted anti-jamming method can obtain effective interference samples in the background of strong clutter and have better anti-jamming performance.