Research On Multiple-radar Signal Level Anti-deception Jamming Under Moving Platform

The radar system is often in a complex electromagnetic environment and is susceptible to various types of interference.The active jammer generates a large number of active false targets by simulating the real target echo,which can confuse or saturate the radar system and has strong deception.Therefore,in complex electromagnetic environment,radar anti-deception ability is an important condition to ensure the normal operation of radar system.Compared with the single station radar,the multi-station radar system has multiple observation angles,which has an innate advantage in the anti-deception jamming.By means of fusion processing,the anti-jamming ability of the radar can be effectively improved.However,multiple jammers can also be linked into a network to greatly improve their deception ability,which brings greater challenges to radar antijamming.In the airborne and shipborne moving platforms,multi-station radar site errors will bring registration errors during signal fusion and affect the performance of synergistic anti-deception jamming.In view of the fact that the current signal-level anti-deception method of multi-station radar only considers a single interference source and does not consider the site error of radar station,this thesis takes multi-deception jamming as the research object and starts with signal-level fusion to make relevant research on the cooperative anti-deception jamming of multi-station radar under the moving platform.The main work contents include:1.The scene of fusion anti-jamming and the mechanism of signal level collaborative antideception interference are introduced.A diversity channel is formed between the transmitting station and the receiving station of multi-station radar,and the radar site error will lead to the difficulty in realizing spatial registration of echoes in different channels.The location of the resolution unit containing the target in each diversity channel is uncertain,which brings challenges for anti-deception jamming.In addition,the cross-sectional area anisotropy of real targets in different channels and the echo correlation coefficient change with the change of observation Angle,while the active false targets do not have this characteristic,which lays a theoretical foundation for the signal level cooperation anti-deception jamming.2.For the multi-interference source scenario,a signal-level cooperative anti-spoofing algorithm based on vector correlation processing of target echo signal is studied.The real target has anisotropy,the echo signal in each diversity channel is de-correlated,and the active false target generated by the same jammer is isotropic,that is,the received signal of each channel is highly correlated.Based on this difference,the target echo signal vector is defined,the correlation difference between different target vectors is analyzed,and the true and false target identification algorithm based on correlation difference is proposed.The correlation coefficient between different targets is calculated,and binary quantization,statistical summation and threshold identification are carried out to identify active false targets.The simulation results show that this method can eliminate the active false targets almost completely and has a high probability of real target identification.The advantages of this method are that it can effectively identify the active false targets generated by any modulation mode and can be used in the case of multiple interference sources.3.Aiming at the problem of discrimination performance degradation caused by registration error in the scene of moving platform,this thesis studies the algorithm of first estimating the target received signal vector and then carrying out signal level collaborative anti-deception based on correlation coefficient.Firstly,the maximum likelihood is used to estimate the location of the target information in the uncertain region with a certain size,namely the registration error,so as to form the target echo vector,and then the true and false targets are identified according to the difference of correlation coefficients.Secondly,when the size of the uncertain area is unknown,the expression of the relation between the registration error and the radar site error is derived.The simulation results show that the proposed method can guarantee a high real target identification probability and an active false target identification probability close to 1 at a higher jammer-to-noise ratio,while the active false target has a low misjudgment probability at a lower jammer-to-noise ratio,and the real target identification probability is not affected.The advantages of this method are as follows:considering the signal-level anti-deception jamming under the registration error,it improves the authenticity and practicability of the signal-level anti-deception jamming model of multi-station radar system.4.According to the proposed signal level anti-deception algorithm,the simulation software system of multi-station radar anti-deception on moving platform is developed based on MATLAB GUI platform.The system can be used to set anti-jamming simulation scenarios for multi-station radars on the mobile platform,and carry out signal level cooperative anti-spoof-type identification,display the tracking track of detected targets before and after jamming identification,and verify the feasibility of active false target identification.In addition,it can evaluate the identification performance of active deception interference under registration errors,and obtain the identification curve of true and false targets under different jammer-to-noise ratio.