Implementation of Er-doped random fiber laser self-mixing sensor with ultra-limit sensitivity

Author:

Hu Jun123ORCID,Li Ruifeng4,Hu Zhijia123,Li Haosen123ORCID,Yang Yaozhong123ORCID,Li Hongtao123ORCID,Lv Jialiang12ORCID,Yu Qi123ORCID,Zhao Yunkun56,Yu Benli123,Lu Liang123ORCID

Affiliation:

1. Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University 1 , Jiulong Road 111#, Hefei 230601, China

2. Key Laboratory of Opto-Electronic Information Acquisition and Manipulation of Ministry of Education, Anhui University 2 , Jiulong Road 111#, Hefei 230601, China

3. School of Physics and Optoelectronic Engineering, Anhui University 3 , Jiulong Road 111#, Hefei 230601, China

4. School of Instrumentation and Optoelectronic Engineering, Beihang University 4 , Beijing 100191, China

5. School of Optics and Photonics, Beijing Institute of Technology 5 , Beijing 100081, China

6. Yangtze Delta Region Academy of Beijing Institute of Technology 6 , Jiaxing 314019, China

Abstract

This study first demonstrates that the random distributed feedback fiber laser (RDFL) can be implemented for sensing detection by using the self-mixing effect as a sensing mechanism. By constructing a compact self-mixing velocimeter based on Er-doped RDFL with the integration of a laser, sensing element, and transmission platform, we successfully measured the minimum detectable feedback intensity of 38.65 fW for the velocity signal, corresponding to 0.55 photons per Doppler cycle, exhibiting ultra-high sensitivity dynamics characteristics. In addition, the velocity measurement of a non-cooperative target at a single-channel distance of 100 km is accomplished because of the natural feature of long-distance transmission for the random distributed feedback fiber lasers, which greatly improves the ultra-long detection range in the field of self-mixing sensing. The proposed sensing scheme not only unveils a fresh perspective on the exploration of random fiber laser sensing but also showcases its diverse and wide-ranging applications within the realm of remote sensing measurements.

Funder

National Natural Science Foundation of China

Publisher

AIP Publishing

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