基于LSTM的辐射源个体识别技术分析

Analysis of SEI Technology Based on LSTM

随着科学技术的快速发展,电磁环境中的信息数据越来越庞杂,如何从复杂的环境中找到并准确识别出有效信息,是辐射源个体识别(SEI)技术研究的目的,而传统的SEI技术已经很难适应当前的复杂环境。阐述了现有SEI技术及其存在的不足,提出了基于长短时记忆(LSTM)神经网络的辐射源个体识别方法,介绍了其原理,并通过仿真分析验证了该方法的可行性,最后提出了后续的技术发展方向。

With the rapid development of science and technology,the information data in the complex electromagnetic environment become increasingly ponderous.How to find and accurately identify the effective information from the complex environment is the research purpose of specific emitter identification(SEI)technology,and the traditional SEI technologies are difficult to adapt to the modern complex environment.This paper explains the existing technology of SEI and its shortcomings,proposes a kind of SEI method based on long short term memory(LSTM)neural network,introduces its principle,and verifies the feasibility through the simulation and analysis,finally proposes the subsequent technical development direction.