改进PSO-VMD结合小波阈值的磁场信号处理方法研究

Research on Magnetic Field Signal Processing Method Based on Improved PSO-VMD and Wavelet Threshold

摘要:

针对室内磁场定位中磁测序列受电磁干扰和噪声影响的问题，提出一种改进粒子群优化变分模态分解结合小波阈值的磁场信号处理方法。通过对磁测序列信号特征的研究，利用改进PSO算法优化VMD的模态个数和惩罚因子，对分解出的模态进行相关系数分析，并基于归一化包络熵和小波分解层级参数对不同频段和噪声水平的信号进行自适应小波阈值改进，实现模态筛选和自适应降噪处理。经仿真信号处理结果表明，该方法在信噪比、相似度、平均绝对误差和均方误差等指标上均优于PSO-VMD重构和PSO-VMD-固定小波阈值方法。在实测磁场序列中，所提方法相较对比方法的信噪比分别提升6.7001dB和4.6568dB，相似度提高1.306%和0.5568%，平均绝对误差和均方误差均显著下降，在室内走廊环境下的实验指标同样验证了所提方法的有效性。该方法能够有效提升磁场信号质量，适用于室内磁测序列信号的分析与处理。

Abstract:

To address the issue of electromagnetic interference and noise in magnetic measurement sequences for indoor magnetic field positioning, an improved particle swarm optimization variational mode decomposition method combined with wavelet thresholding is proposed for magnetic field signal processing. Based on the study of magnetic measurement sequence signal characteristics, an improved PSO algorithm is utilized to optimize the number of modes and penalty factors in VMD. Correlation coefficient analysis is conducted on the decomposed modes, and an adaptive wavelet thresholding improvement is introduced based on normalized envelope entropy and wavelet decomposition level parameters to process signals with different frequency bands and noise levels, thereby achieving mode selection and adaptive noise reduction. Simulation results demonstrate that the proposed method outperforms PSO-VMD reconstruction and PSO-VMD with fixed wavelet thresholding in terms of SNR, similarity, MAE, and MSE. In real magnetic field sequence measurements, compared with the reference methods, the proposed method improves SNR by 6.7001 dB and 4.6568 dB, increases similarity by 1.306% and 0.5568%, and significantly reduces MAE and MSE. The experimental results in an indoor corridor environment further validated the effectiveness of the proposed method. This method can effectively enhance the quality of magnetic field signals and is suitable for the analysis and processing of indoor magnetic measurement sequences.