基于遥测信号多模态特征的卫星个体识别方法  

Individual Satellite Identification Method Based on Multimodal Features of Telemetry Signals

作　　者：吕青 孟京龙 李诗瑶 张毅 刘何帅 LYU Qing;MENG Jinglong;LI Shiyao;ZHANG Yi;LIU Heshuai(United Laboratories of TT&C and Communication,Jiuquan Satellite Launch Center,Jiuquan 732750,Gansu,China;School of Electronic Engineering,Xidian University,Xi’an 710071,Shaanxi,China)

机构地区：[1]酒泉卫星发射中心测控通信联合实验室,甘肃酒泉732750 [2]西安电子工程大学电子工程学院,陕西西安710071

出　　处：《上海航天(中英文)》2024年第6期14-22,共9页Aerospace Shanghai(Chinese&English)

摘　　要：随着航天技术发展,太空已经成为战略焦点,空间目标态势感知尤为关键,其中包括卫星的电磁频谱检测及个体识别。遥测信号是卫星在轨运行的常见辐射源信号,通过深入分析卫星遥测信号中的潜在特征,可以有效地辨识卫星个体目标。本文提出了一种基于多模态融合的识别方法,结合了残差卷积网络、长短期记忆网络,强化了网络对于信号数据深度特征的提取与融合能力,显著提高了识别的准确性。实验测试显示,所提方法在实测数据集上达到了92%的平均识别准确率。本研究对卫星个体识别技术的发展具有指导意义,有望推进该领域的进一步研究和应用。With the development of aerospace technology,space has become a strategic focus,and the perception of spatial targets is particularly crucial,including the detection of satellite electromagnetic spectra and individual satellite identification.Telemetry signals are common radiation source signals for satellites in orbit,and individual satellite targets can be effectively identified by in-depth analyses on the potential features in their telemetry signals.In this paper,an identification method based on multi-modal fusion is proposed.It combines residual convolutional networks and long short-term memory(LSTM)networks,and can enhance the network's ability to extract and fuse deep features of signal data,significantly improving the identification accuracy.Experimental tests show that the proposed method achieves an average identification accuracy of 92%on the actual data set.This study has guiding significance for the development of satellite individual identification technology,and is expected to promote further research and application in this field.

关 键 词：态势感知 深度学习 空间目标识别 信号特征分析 多模态特征提取 

分 类 号：TN911.72[电子电信—通信与信息系统]