Method Recogniting the Jamming to Pulse Radars Based on Improved MobileV3Net
With the rapid development of modern electronic warfare,new types of jamming based on digital radio frequency memory forwarding are emerging in an endless stream.How to quickly and effectively identify this kind of jamming has become a hot issue in current research.In view of this,this paper proposes a research into the recognition of pulse radar jamming based on improved Mo-bileV3Net.In the research,MobileV3Net is used as the basic network framework,and a dynamic convolution module and an efficient channel attention module are added,then the effective recogni-tion of eight types of jamming under small samples with automatic extraction features is realized.The simulation results show that the training time of the network is greatly reduced,the recogni-tion accuracy can still maintain more than 95％under lightweight training samples,and the average recognition rate is more than 99％in-10～10 dB,which proves that the method has more robust-ness,higher accuracy and better lightweight.
radar active jammingtime/frequency domain analysisconvolutional neural networkdynamic convolution
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