XING Shujian; WANG Furong; WANG Yizhao; CHANG Mengfei

doi:10.7498/aps.74.20250024

Abstract

In industrial sites and outdoor long-distance measurements, the difficulty in accurately measuring and correcting the refractive index of air is a critical factor affecting precise distance measurement. In order to develop a simple, long-range, and high-precision absolute distance measurement technique, in this work an absolute distance measurement method is presented based on multi-pulse spectral interferometry by using an optical frequency comb. This method can dynamically correct the measurement errors introduced by group refractive index fluctuations. Firstly, a mathematical model for multi-pulse spectral interferometry is established. By performing a single Fourier transform on the multi-pulse spectral interference signal, the time delay measured in the pseudo-time domain can be used to simultaneously determine the group refractive index of the measurement path and the measured distance. Secondly, by fine-tuning the repetition frequency and using difference computation, the measurement range can be extended from the non-ambiguity range of traditional spectral interferometry to arbitrary lengths. Finally, extensive numerical simulations and analyses are conducted to validate the performance of the proposed method. The simulation results demonstrate that with a reference distance of 0.1 m, the maximum absolute error in group refractive index measurement is 0.12×10^–6, and the maximum distance measurement error is 33 nm in a range of 0—200 m. In order to measure the group refractive index in real time under changing atmospheric conditions and compensate for ranging errors caused by changes in air refractive index, even under changing atmospheric conditions, the maximum distance measurement error is 38 nm, ensuring sub-micron-level measurement accuracy over long distances. The research results indicate that this method can be applied to large-scale and high-precision absolute distance measurement.

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Corresponding author: XING Shujian, xingshujian521@163.com

Funds: Project supported by the Fundamental Research Funds for the Central Universities, China (Grant No. 3122019054).

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Vol. 74, Issue 7 - 2025-04-05

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