基于增强相位解调结构的光纤声传感系统动态范围的改进

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Haojie Wu;Zhijuan Zhu;Qidong Bao;Wenrui Wang;Lingyun Ye;Kaichen Song;Xinglin Sun
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引用次数: 0

摘要

大动态范围(DR)是光纤声传感系统的主要要求之一,其中声信号被转换成调相(PM)信号进行检测。在信号转导阶段,进行了提高相位灵敏度的研究。这允许将声信号转换为具有更高相位调制指数(pmi)的PM信号,从而改进对弱声信号的检测。然而,强声信号引起的高pmi相应地拓宽了信号带宽。为了解决相位解调噪声与带宽之间的矛盾,本文提出了一种具有增强相位采集方法和增强反馈控制算法的新型相位解调结构。增强型相位采集方法将高精度模数转换器(ADC)采样数据与高频比较器数据相结合,增强了捕获动态相位变化的能力。增强反馈控制算法结合了一种基于高阶信号模型的预测控制方法和卡尔曼滤波(KF)迭代来优化相位跟踪性能。该解调结构减小了残差信号的相位变化,在采样前压缩了残差信号的带宽。这种组合方法有效地平衡了噪声和带宽。通过仿真和实验验证了该结构的性能,在1 kHz时实现了170.1 dB的DR,实际测试中的相位分辨率为$4 \乘以10^{-{6}}$ rad/ $ \sqrt {\text {Hz}} $。根据我们的估计,在1khz时,最佳DR约为211.5 dB。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Dynamic Range in Fiber-Optic Acoustic Sensing Systems With Enhanced Phase Demodulation Structure
Large dynamic range (DR) is one of the primary requirements in fiber-optic acoustic sensing systems, wherein acoustic signals are converted into phase-modulated (PM) signals for detection. In the signal transduction stage, research has been conducted to increase the phase sensitivity. This allows for the conversion of acoustic signals into PM signals with higher phase modulation indices (PMIs), therefore improving the detection of weak acoustic signals. However, higher PMIs induced by strong acoustic signals correspondingly broaden the signal bandwidth. A phase demodulation structure that provides both high-bandwidth capability and low-noise performance is needed to improve both the upper and lower limits of DR. To solve the contradiction between phase demodulation noise and bandwidth, we proposed a novel phase demodulation structure featuring an enhanced phase acquisition method and an enhanced feedback control algorithm. The enhanced phase acquisition method combines high-precision analog-to-digital converter (ADC) sampling data with high-frequency comparator data, enhancing the capability to capture dynamic phase variations. The enhanced feedback control algorithm incorporates a predictive control method using high-order signal models and Kalman filter (KF) iteration to optimize the phase tracking performance. With the proposed demodulation structure, phase variation in the residual signal is reduced and the residual signal bandwidth is compressed before sampling. This combined approach effectively balances noise and bandwidth. The performance of the proposed structure is validated through simulations and experiments, achieving a DR of 170.1 dB at 1 kHz with a phase resolution of $4 \times 10^{-{6}} $ rad/ $ \sqrt {\text {Hz}} $ in practical tests. Based on our estimation, the optimal DR is approximately 211.5 dB at 1 kHz.
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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