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利用频谱地图重构的辐射源识别

王雪刚 王方刚 王意卓

王雪刚, 王方刚, 王意卓. 利用频谱地图重构的辐射源识别[J]. 电子与信息学报. doi: 10.11999/JEIT240050
引用本文: 王雪刚, 王方刚, 王意卓. 利用频谱地图重构的辐射源识别[J]. 电子与信息学报. doi: 10.11999/JEIT240050
WANG Xuegang, WANG Fanggang, WANG Yizhuo. Specific Emitter Identification Using Radio Environment Map Reconstruction[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240050
Citation: WANG Xuegang, WANG Fanggang, WANG Yizhuo. Specific Emitter Identification Using Radio Environment Map Reconstruction[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240050

利用频谱地图重构的辐射源识别

doi: 10.11999/JEIT240050
基金项目: 中央高校基本科研业务费(2022JBQY004),国家重点研发计划(2020YFB1806903),国家自然科学基金(62221001),国家自然科学基金铁路基础研究联合基金(U2368201)
详细信息
    作者简介:

    王雪刚:男,博士生,研究方向为频谱感知、信号识别

    王方刚:男,教授,研究方向为宽带移动通信系统与专用移动通信、信息处理与人工智能

    王意卓:男,研究方向为无线通信与信号处理

    通讯作者:

    王方刚 wangfg@bjtu.edu.cn

  • 中图分类号: TN911.7

Specific Emitter Identification Using Radio Environment Map Reconstruction

Funds: The Fundamental Research Funds for the Central Universities (2022JBQY004), The National Key R&D Program of China (2020YFB1806903), The National Natural Science Foundation of China (62221001), The Joint Funds for Railway Fundamental Research of National Natural Science Foundation of China (U2368201)
  • 摘要: 无线环境地图(REM)是呈现电磁态势的一种有效形式,考虑实际观测的不完整频谱地图受到干扰和噪声污染的问题,该文对频谱地图进行重构,并在此基础上完成辐射源识别。首先,将复杂电磁环境下的频谱地图建模为高维张量,在预处理中通过线性插值对其初始化补全。然后,使用视觉Transformer模型解决语义分割问题以识别频谱语义区域,区域中仅单一辐射源功率占主导,每个语义张量的低秩性得以保留。提出了一种压缩式张量分解算法,并采用交替方向乘子法(ADMM)在语义区域中重构期望信号频谱和干扰;最后,在重构的频谱地图上检测未知辐射源的位置。该方法能够充分利用频谱数据的低秩性,适用于广域多辐射源个体的电磁场景。实验结果表明,所提方法比现有方法具有更优的重构性能,降低了达到相同频谱地图恢复精度时对观测样本比例的要求,并能够准确检测辐射源。
  • 图  1  频谱地图重构示意图

    图  2  基于 ViT 的频谱语义分割模型结构

    图  3  不同算法频谱地图重构性能

    图  4  基于语义分割的频谱重构算法收敛性

    图  5  辐射源检测性能比较

    1  基于语义分割的频谱地图重构算法

     输入:初始补全张量$ {{\tilde{ {\boldsymbol{\mathcal{Y}}}}}_m} $,语义标签$ {{{\boldsymbol{\mathcal{L}}}}_m} $, $ m \in {{\mathcal{I}}_M} $,迭代次数K
     输出:重构的期望频谱$ {\tilde {\boldsymbol{\mathcal{X}}}} $;
     初始化:$ {\tilde{ {\boldsymbol{\mathcal{X}}}}}_m^{(1)} = {\bf{0}} $, $ {\tilde {{\boldsymbol{\mathcal{S}}}}}_m^{(1)} = 0 $, $ {\lambda ^{(1)}} = 0 $, $ {\beta ^{(1)}} = {10^{ - 6}} $,
     $ {\beta _{\max }} = {10^{10}} $, $ \rho = 1.2 $,m = 1, $ k = 1 $;
     (1) 当$ ||{{\boldsymbol{\mathcal{X}}}_m}||_{{\mathrm{F}}} ^2 $未收敛且$ k < K $,重复步骤(2)~(7);
     (2  使用式(22)更新$ {\boldsymbol{\mathcal{X}}}_m^{(k + 1)} $;
     (3)  使用式(24)更新$ {{\boldsymbol{\mathcal{S}}}}_m^{(k + 1)} $;
     (4)  使用式(25)更新$ \lambda _m^{(k + 1)} $;
     (5)  使用式(26)更新$ c_m^{(k + 1)} $;
     (6)  $ {\beta ^{(k + 1)}} = \min \{ \rho {\beta ^{(k)}},{\beta _{{\text{max}}}}\} $;
     (7)  k = k+1;
     (8) m = m+1;
     (9) 重复步骤(1)、(8),直到m = M
     (10) $ {\tilde {\boldsymbol{\mathcal{X}}}}{\text{ = }}\displaystyle\sum\nolimits_{m = 1}^M {{{\boldsymbol{\mathcal{X}}}_m} \odot } {{{\boldsymbol{\mathcal{L}}}}_m} $。
    下载: 导出CSV
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出版历程
  • 收稿日期:  2024-01-24
  • 修回日期:  2024-07-16
  • 网络出版日期:  2024-07-24

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