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引用本文：

马松,刘田,尚建忠,等.语义分割网络下的混合信号频谱分离[J].电讯技术，2020，（4）： - . [点击复制]
MA Song,LIU Tian,SHANG Jianzhong,et al.Spectra Separation via Semantic Segmentation Network[J].，2020，（4）： - . [点击复制]

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语义分割网络下的混合信号频谱分离
马松,刘田,尚建忠,余湋,穆航,陈霄南,王军
0 字体:加大+\|默认\|缩小-
(中国西南电子技术研究所，成都 610036;西安卫星测控中心，西安 710043;电子科技大学通信抗干扰技术国家级重点实验室，成都 611731)

摘要:

单通道接收机下，多个时频混合信号的分离属于非稀疏欠定信号分离问题，难以求解。针对这类非稀疏欠定信号分离问题，提出了一种基于语义分割网络、从频域实现多个指定类别信号分离的新方法。利用语义分割网络提取信号的频域分布特征，克服了单通道接收机下信号先验信息过少的问题。仿真表明，该方法具有较高的分离精度，且响应时间短，可用于单通道接收机中时频混叠信号的分离。

关键词: 信号分离语义分割网络非稀疏欠定信号分离

DOI：

基金项目:

Spectra Separation via Semantic Segmentation Network

MA Song,LIU Tian,SHANG Jianzhong,YU Wei,MU Hang,CHEN Xiaonan,WANG Jun

(Southwest China Institute of Electronic Technology，Chengdu 610036，China;China Xi′an Satellite Control Center, Xi′an 710043,China;National Key Laboratory of Communication,University of Electronic Science and Technology of China,Chengdu 611731,China)

Abstract:

Separating multiple time-frequency aliasing signals via a single channel receiver is a non-sparse underdetermined signal separation (NUSS) problem,which is hard to tackle.In this paper,a new semantic segmentation network (SSN) based method is proposed to separate multiple specific time-frequency aliasing signals in frequency domain.By using a well-designed SSN,the frequency distribution features of each signal component are extracted to combat with the lack of prior information of signal sources via a single channel receiver.Simulation results show that the proposed method achieves desirable separation accuracy with short response time,which can be applied to multiple time-frequency aliasing signals’ separation for a single channel receiver.

Key words: signal separation semantic segmentation network non-sparse underdetermined signal separation