基于无监督变异自动编码器的联合通信和雷达系统中的信号源分离

IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Open Journal of Vehicular Technology Pub Date : 2023-11-22 DOI:10.1109/OJVT.2023.3335358
Khaled A. Alaghbari;Heng Siong Lim;Benzhou Jin;Yutong Shen
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引用次数: 0

摘要

混合信号在时频域中的源分离是联合通信和雷达(JCR)系统实现所需性能的关键,特别是在低信噪比(SNR)下。在本文中,我们建议使用生成模型,如无监督变分自编码器(VAE),来分离传感和数据通信信号。首先分析了采用不同掩模技术的VAE系统;然后,选择最佳技术与常用的盲源分离(BSS)算法进行比较。我们通过采用不同的指标,如信失真比(SDR)、源干扰比(SIR)和源伪比(SAR)来验证所提出的VAE的性能。仿真结果表明,在低信噪比的时频混合信号和高、低信噪比的时频混合信号中,VAE的性能都优于BSS技术。它使JCR系统在具有挑战性的第一种场景中分别获得11.1 dB和6db的SDR增益,用于恢复传感和数据通信信号,信噪比为0 dB。最后,我们分析了JCR系统在检测同一频段干扰信号方面的鲁棒性,仿真结果表明,基于所提出的步骤,JCR系统的检测精度达到91%。
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Source Separation in Joint Communication and Radar Systems Based on Unsupervised Variational Autoencoder
Source separation of a mixed signal in the time-frequency domain is critical for joint communication and radar (JCR) systems to achieve the required performance, especially at a low signal-to-noise ratio (SNR). In this paper, we propose the use of a generative model, such as the unsupervised variational autoencoder (VAE), to separate sensing and data communication signals. We first analyse the VAE system using different mask techniques; then, the best technique is selected for comparison with popular blind source separation (BSS) algorithms. We verify the performance of the proposed VAE by adopting different metrics such as the signal-to-distortion ratio (SDR), source-to-interference ratio (SIR), and sources-to-artifacts ratio (SAR). Simulation results show that the proposed VAE outperforms the BSS techniques at low SNR for the case of a mixed signal in the time-frequency domain and at low and high SNR for a mixed signal in the time domain. It enables the JCR system in the challenging first scenario to obtain SDR gains of 11.1 dB and 6 dB at 0 dB SNR for recovering the sensing and data communication signals respectively. Finally, we analyse the robustness of the JCR system in detecting an interference signal operating in the same frequency band, where the simulation result indicates an accuracy of 91% based on the proposed steps.
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CiteScore
9.60
自引率
0.00%
发文量
25
审稿时长
10 weeks
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