Research On The Recognition Of Stealth Target By Cognitive Radar

In recent years,stealth technology has developed rapidly and occupied an irreplaceable position in the war environment,so the research on anti-stealth technology is even more urgent.Cognitive radar not only has the ability to perceive the corresponding changes in the environment,but also has the advantage of dealing with adaptive and self-improving ability.The application of cognitive radar in anti-stealth technology enables it to make self-adjustment according to the perception of the environment so as to greatly improve the anti-stealth ability.This article will study the cognitive radar stealth targets,the method of build cognitive radar recognition-feedback-decision-response of the closed-loop system,put forward a kind of cognitive radar tracking framework to recognize the stealth target,the distributed kalman filter(DKF)algorithm solution into the netted radar stealth target recognition,so as to better improve radar target recognition and detection capabilities.In this paper,a nature inspired method to optimize the stealth target waveform is proposed.Physic optics(PO)method is used to construct the Radar cross-section(RCS)model of stealth target F-35.We find the best observation Angle of the RCS,and deploy the cognitive radar.The beetle antennae search(BAS)algorithm is proposed to optimize the transmitted waveform,instead of using the traditional semi-definite relaxation(SDR).Simulation results show that compared with SDR method,BAS algorithm can improve radar identification performance by optimizing emission waveform.In order to better track and identify stealth targets,this paper further discusses the tracking scenarios of bistatic radar and multi-base radar,proposes the deployment of multi-base radar at several optimal observation angles of RCS,and adopts DKF method for information fusion,so as to further improve the recognition performance.Simulation results show that compared with bistatic radar,the multi-base tracking and identification method proposed in this paper can improve the tracking performance of stealth target.