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基于飞秒光学频率梳的色散干涉测量法的距离测量改进

Improvement of Distance Measurement Based on Dispersive Interferometry Using Femtosecond Optical Frequency Comb.

作者信息

Niu Qiong, Song Mingyu, Zheng Jihui, Jia Linhua, Liu Junchen, Ni Lingman, Nian Ju, Cheng Xingrui, Zhang Fumin, Qu Xinghua

机构信息

State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin 300072, China.

出版信息

Sensors (Basel). 2022 Jul 20;22(14):5403. doi: 10.3390/s22145403.

DOI:10.3390/s22145403
PMID:35891083
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9318693/
Abstract

Since the dispersive interferometry (DPI) based on optical frequency combs (OFCs) was proposed, it has been widely used in absolute distance measurements with long-distance and high precision. However, it has a serious problem for the traditional DPI based on the mode-locked OFC. The error of measurements caused by using the fast Fourier transform (FFT) algorithm to process signals cannot be overcome, which is due to the non-uniform sampling intervals in the frequency domain of spectrometers. Therefore, in this paper, we propose a new mathematical model with a simple form of OFC to simulate and analyze various properties of the OFC and the principle of DPI. Moreover, we carry out an experimental verification, in which we adopt the Lomb-Scargle algorithm to improve the accuracy of measurements of DPI. The results show that the Lomb-Scargle algorithm can effectively reduce the error caused by the resolution, and the error of absolute distance measurement is less than 12 μm in the distance of 70 m based on the mode-locked OFC.

摘要

自从基于光学频率梳（OFC）的色散干涉测量法（DPI）被提出以来，它已被广泛应用于长距离、高精度的绝对距离测量中。然而，基于锁模OFC的传统DPI存在一个严重问题。使用快速傅里叶变换（FFT）算法处理信号所导致的测量误差无法克服，这是由于光谱仪频域中的采样间隔不均匀。因此，在本文中，我们提出了一种形式简单的OFC新数学模型，用于模拟和分析OFC的各种特性以及DPI的原理。此外，我们进行了实验验证，采用了 Lomb-Scargle算法来提高DPI测量的精度。结果表明，Lomb-Scargle算法可以有效减少分辨率引起的误差，基于锁模OFC在70米距离处的绝对距离测量误差小于12微米。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/f675b14ee90e/sensors-22-05403-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/e7cb1361198d/sensors-22-05403-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/96127de2a6c2/sensors-22-05403-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/41b8466dc22a/sensors-22-05403-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/b53a050cb40b/sensors-22-05403-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/0f69b5060f04/sensors-22-05403-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/a2bc8477ffb3/sensors-22-05403-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/4aac105b1b01/sensors-22-05403-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/165e35a4485a/sensors-22-05403-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/f675b14ee90e/sensors-22-05403-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/e7cb1361198d/sensors-22-05403-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/96127de2a6c2/sensors-22-05403-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/41b8466dc22a/sensors-22-05403-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/b53a050cb40b/sensors-22-05403-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/0f69b5060f04/sensors-22-05403-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/a2bc8477ffb3/sensors-22-05403-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/4aac105b1b01/sensors-22-05403-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/165e35a4485a/sensors-22-05403-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f896/9318693/f675b14ee90e/sensors-22-05403-g009.jpg

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