基于矢量阅读器的声表面波传感器频率估计优化

Optimization of Frequency Estimation for Surface Acoustic Wave Sensor Based on Vector Reader

摘要:

在进行无线无源声表面波（SAW）传感器测量时，谐振频率估计的稳定性不佳会限制声表面波阅读器测量系统的性能。为提高频率估计的稳定性，基于传统功率谱频率估计方法引入了相位检波技术，设计了一种矢量阅读器架构以获取矢量频谱，并提出了一种结合相位测量和滤波处理的优化方法。该方法采用逆快速傅里叶变换（IFFT）和有限冲激响应（FIR）滤波方法提升回波信号的信噪比，并结合多种模型拟合方法，针对不同峰型特征的谐振频率进行优化估计。为验证该方法的有效性，构建了 SAW 传感器无线无源测试平台，并开展了无线频率测试实验。采集多组 SAW 回波信号数据进行处理。实验结果表明，经过滤波处理后，回波信号的信噪比提升了约 17 dB，而结合拟合方法优化后，谐振频率估计的标准差低于 0. 5 kHz。该方法能有效提高声表面波阅读器系统的频率估计灵敏度和稳定性。

Abstract:

Poor stability of resonant frequency estimation during wireless passive surface acoustic wave （SAW） sensor measurements can limit the performance of SAW reader measurement systems. To improve the stability of frequency estimation， in this study， a vector reader architecture is proposed based on traditional power spectrum frequency estimation methods. Furthermore， phase detection technology is introduced to obtain vector spectra. Additionally， an optimization method combining phase measurement and filtering processing is proposed. This method uses inverse fast Fourier transform （IFFT） and finite impulse response （FIR） filtering methods to improve the signalto-noise ratio of the echo signal， and it combines multiple model fitting methods to optimize the estimation of resonance frequencies for different peak characteristics. To verify the effectiveness of this method， a wireless passive testing platform for SAW sensors was constructed， and wireless frequency testing experiments were conducted to acquire multiple sets of SAW echo signal data for processing. The experimental results show that after filtering， the signal-tonoise ratio of the echo signal is improved by approximately 17 dB. After further optimization with fitting methods， the standard deviation of resonant frequency estimation is reduced to below 0. 5 kHz， indicating that this method effectively improves the frequency estimation sensitivity and stability of the surface acoustic wave reader system.