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本文提出了一种基于奇异值分解(SVD)正则化和快速迭代收缩阈值算法(FISTA)的单层无相位辐射源重构算法. 该方法能够有效地识别集成电路中的电磁干扰源. 首先, 通过近场扫描获取电磁场数据, 随后利用源重构方法(SRM)在其表面重建等效偶极子模型. 引入SVD正则化项以提高算法的稳定性和抗噪声能力, FISTA技术则加速了算法的收敛速度. 为了验证该方法的准确性和对高斯噪声的鲁棒性, 进行了贴片天线仿真分析和芯片实验测试. 结果表明, 该算法在第35次迭代时达到稳定, 重构结果与仿真结果的相对误差为2.3%, 迭代时间仅为传统方法的61.7%, 相对误差减少了52%.
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关键词:
- 奇异值分解 /
- 快速迭代收缩阈值算法 /
- 近场扫描 /
- 辐射源重构
An algorithm of reconstructing phaseless radiation source based on singular value decomposition (SVD) regularization and fast iterative shrinkage-thresholding algorithm (FISTA) is proposed in this work, aiming at efficiently identifying electromagnetic interference (EMI) sources in integrated circuits (ICs). The method acquires electromagnetic field data through near-field scanning and reconstructs an equivalent dipole array on the surface of the radiation source by using the source reconstruction method (SRM). In the reconstruction process, the SVD regularization term enhances the algorithm's stability and noise resistance, while the FISTA accelerates the convergence speed. In order to validate the effectiveness of the proposed method, dipole array reconstruction is first performed using near-field data at a height of 5 mm for a patch antenna simulation model, followed by analyzing the magnetic field data at a 10 mm validation plane. At the 35th iteration, the total relative error of the reconstruction is 1.21%. The influence of the regularization parameter α on the result is then investigated, and it is found that when α = 0.05 the error is minimized. The method is also tested under different Gaussian white noise conditions, and the relative error is kept below 5%, which demonstrates strong robustness. Finally, the experiments on chips are conducted to verify the method. The proposed method converges stably within 35 iterations, with a relative error of 2.3% in the reconstruction results. The proposed method reduces the total iteration time to 61.7% of the single-layer phaseless interpolation algorithm, while achieving a 52% lower relative error than the double-layer phasless iteration algorithm. The experimental results show that the proposed method can reconstruct phaseless radiation source efficiently and accurately, and has good noise robustness, which is suitable for EMI analysis in ICs. -
Keywords:
- aingular value secomposition (SVD) /
- fast iterative shrinkage-thresholding algorithm (FISTA) /
- near-field scanning (NFS) /
- source reconstruction method (SRM)
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图 7 在不同水平的高斯白噪声下z = 12 mm, f = 2.5 GHz磁场|Hx|幅值 (a) SNR = 30 dB; (b) SNR = 20 dB; (c) SNR = 10 dB; (d) SNR = 5 dB
Fig. 7. Magnetic field $ \left|{H}_{x}\right| $ amplitude under different levels of white Gaussian noise, z = 12 mm, f = 2.5 GHz: (a) SNR = 30 dB; (b) SNR = 20 dB; (c) SNR = 10 dB; (d) SNR = 5 dB.
表 1 与现有方法的时间和相对误差进行对比
Table 1. Comparison of time and relative error with existing methods.
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