Research On The Simulation Technology Of Radio Fuze Anti-chaf Interference

Airborne chaff bomb scatters formation of the chaff cloud is air-to-air missiles,air defense missile radio fuse are faced with the common interference pattern,the near field,local irradiation conditions,based on the echo signal amplitude and frequency characteristics of radio fuse signal processing method is difficult to differentiate the real-time and reliable target and the chaff cloud echo,the serious influence the efficiency of the missile fuse-warhead system,therefore,chaff interference radio fuse is faced with a difficult problem to be solved.Chaff interference based on radio fuse technology as the background,under the action of the fixed wing aircraft wake chaff cloud movement modeling and visualization simulation technology,chaff and typical target echo signal simulation technology,the chaff cloud echo signal recognition based on machine learning technology based on FPGA,chaff interference performance evaluation system of radio fuse design,etc.Carried on the thorough and systematic research.The main work of this paper is as follows:Based on aerodynamic theory,this paper proposes a fixed wing aircraft wake chaff cloud movement under the action of diffusion model,and based on C++ Builder integrated development environment to develop the fixed wing aircraft wake under the action of chaff cloud visual simulation and the chaff cloud echo signal simulation calculation software radio fuse,implements the scatters patterns and different intersection under the condition of the chaff cloud echo signal simulation calculation.Based on physical optics method,equivalent electromagnetic flow method and regional projection/physical optics method,the visual simulation software of target echo signal was developed,and the simulation calculation of typical target echo signal under different rendezvous conditions was realized.An anti-chaff interference method for radio fuse based on machine learning was proposed.A convolutional neural network model and a support vector machine model were studied and constructed.The neural network and support vector machine were trained and classified by using the chaff/target measured and simulated echo data.The chaff cloud recognition signal processing prototype based on Xilinx ZYNQ-7000 series FPGA chips was developed,the corresponding chaff cloud recognition host computer software was developed,the radio fuse anti-chaff interference performance evaluation system was built,and the chaff cloud echo signal recognition accuracy,signal processing time and other key indicators were tested.