| 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： |
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| 基金项目: |
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| 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 |
