Fast Recognition Algorithm of Active Deception Jamming Based on Deep Metric Learning
The accurate recognition of jamming is the key premise of jamming suppression,but in the process of active deception jamming recognition,the single jamming with similar shape is easy to confuse,and the recognition rate of compound jamming is not high.To solve this problem,this paper proposes an active deception jamming recognition algorithm based on deep metric learning.The method trains a deep metric learning network by using a smooth pseudo Wigner-Ville distribution(SPWVD)of jamming sig-nals as time-frequency feature samples,and the image features were optimized by the joint constraint of hash algorithm and"cross-entropy loss function-triplet loss function-center loss function"to enhance the discrimination ability of the deep metric learning network for subtle differences in time-frequency distribu-tion.Simulation results show that the trained deep metric learning network can quickly and accurately identify 8 kinds of single jamming and 3 kinds of compound jamming,with an average recognition accura-cy of 99.36％,and still maintain good performance under the condition of a small number of samples.
active deception jammingjamming recognitiondeep metric learningloss functiontime-frequency distribution
NETL
NSTL
万方数据
