基于频率敏感注意力的短波宽带特定信号检测
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作者单位:

1.山东大学信息科学与工程学院,青岛 266237;2.中国电波传播研究所,青岛 266107;3.中国人民解放军61680部队,青岛 266207

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山东省自然科学基金(ZR2020MF004);中国电波传播研究所稳定支持科研经费项目(KFW20210261)。


Shortwave Wideband Specific Signal Detection Based on Frequency-Sensitive Attention
Author:
Affiliation:

1.School of Information Science and Engineering, Shandong University, Qingdao 266237, China;2.China Research Institute of Radiowave Propagation, Qingdao 266107, China;3.Unit 61680 of PLA, Qingdao 266207, China

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    摘要:

    为提高短波复杂电磁环境下特定信号检测识别准确率,提出了一种基于频率敏感注意力的短波宽带特定信号检测算法。依据短波特定信号在时频图中时间方向上的相关性和频率方向上的局部性,设计了一种具有窄长形状感受野的频率敏感注意力机制,通过将特征图沿时间轴方向进行条块分割并在条块内计算自注意力,捕获时间轴方向的远距离依赖关系并限制频率轴方向感受范围,并以此为基础构建了一种端到端的短波特定信号检测器频率敏感信号检测器(Frequency sensitive signal detector,FSSDet)。以短波宽带信号时频图为输入,FSSDet可直接输出多个特定信号的调制类型及起止时间、中心频率和带宽等重要参数信息。在包含8类47 880个样本的仿真数据集上进行实验,所提方法在0 dB以上的平均精度均值(mean Average precision, mAP)高达98.5,在信噪比低至-10 dB时仍高于72.5。结果表明,所提方法具有较高的短波特定信号检测识别准确率,在低信噪比下具备良好的鲁棒性。

    Abstract:

    A shortwave wideband specific signal detection algorithm based on frequency-sensitive attention is proposed to improve the accuracy of specific signal detection and recognition in a shortwave complex electromagnetic environment. A frequency-sensitive attention mechanism with a narrow and long shape receptive field is designed based on the correlation in the time direction and the locality in the frequency direction of shortwave specific signals in the spectrogram, and an end-to-end shortwave specific signal detector frequency sensitive signal detector (FSSDet) is constructed on this basis by segmenting the feature map into strip block along the time-axis direction and calculating the self-attention in the strip block, capturing the long-distance dependence in time-axis direction and limiting the sensing range in frequency-axis direction. FSSDet can directly output the modulation type of several specific signals, as well as important parameter information such as start and end time, center frequency, and bandwidth when a spectrogram of a shortwave wideband signal is given as input. Experiments are carried out on a simulation dataset of 47 880 samples from eight classes, and the proposed method has mean average precision (mAP) as high as 98.5 above 0 dB and remains above 72.5 when the signal noise ratio (SNR) is as low as -10 dB. The results show that the proposed method detects and recognizes short wave specific signals with high accuracy and robustness under low SNR.

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耿频永,曹叶文,赵晓蕾,李振星,张新斌.基于频率敏感注意力的短波宽带特定信号检测[J].数据采集与处理,2023,38(1):63-73

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  • 收稿日期:2022-09-13
  • 最后修改日期:2022-11-29
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  • 在线发布日期: 2023-01-25