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Improving Sensing Measurements Using Laser Self-Mixing Interference in Non-Line-of-Sight Optical Communication via Systems

Sichen Lu, Changying Guo

Abstract


Objective: Mobile robots leverage laser self-mixing interference for sensing in non-line-of-sight optical communications, allowing for a wide range of measures such as distance, velocity, and displacement, while also improving accuracy and flexibility in robotic navigation and interaction. Interference, restricted range, and sensitivity to environmental factors are challenges that affect the precision and reliability of sensing measures. Methods: This paper presents a detailed introduction to theory and various algorithms of channel estimation in wireless communication. Combining the characteristics of UV channels, a channel estimation algorithm suitable for UV optical communication systems is selected, and relevant simulations are carried out. A theoretical analysis of channel estimation SNR and a proposed angle measurement method using laser self-mixing interference are discussed. A device is designed to implement this method, utilizing self-mixing interferometric fringe counting to measure rotation displacement in mobile robots. Findings: In results, sensing measurement and modality are employed for SNR and robotic localization performance. Distance (15 dB), velocity (12 dB), and object shape (18 dB) in SNR and laser range finder (5 cm), camera (15 cm), and LiDAR (3 cm) in robotic localization performance. Conclusion: Incorporating laser self-mixing interference effects into non-line-of-sight optical communication for mobile robotics enhances sensing precision across diverse measurements, fostering robustness and adaptability in dynamic environments.

 

Doi: 10.28991/HIJ-2024-05-04-012

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Keywords


Mobile Robots; Displacement Measurement; Non-Line-of-Sight Optical Communication Signal Processing; Systems, Channel Estimation; Optical Feedback Self-Mixing Interference; Angle Measurement.

References


Li, W., Zhou, Y., Du, W., Peng, Y., & Li, J. (2021, April). Application of the precision industrial measurement technology in geometric measurement. IOP Publishing: Journal of Physics: Conference Series, 1885 (2), 022021. doi:10.1088/1742-6596/1885/2/022021.

Tao, C., Wu, Y., Wang, W., Qian, Y., Tao, R., & Kang, T. (2019). Experimental investigation of white-light interferometry based on sub-dark-field illumination. Optics Communications, 435, 108-117. doi:10.1016/j.optcom.2018.11.020.

Huang, Z., Nie, Z., Xu, H., Zhao, S., Chen, G., Hu, X., ... & Li, D. (2024). A Multilongitudinal Mode Quadrature Laser Self-Mixing Vibration Sensor for Fault Diagnosis of Bearing. IEEE Sensors Journal, 24(4), 4407-4417. doi:10.1109/JSEN.2023.3348143.

Hu, L., & Dai, S. (2022). Nano-semiconductor materials. Dye-sensitized Solar Cells, 7, 41. doi:10.1515/9783110344363.

Zhang, P. C., & Xu, D. (2015). Tracking and guiding multiple Laser beams for beam and target alignment. International Journal of Automation and Computing, 12(6), 600-610. doi:10.1007/s11633-015-0908-8.

Chen, L., Zhang, D., Zhou, Y., Liu, C., & Che, S. (2018). Design of a high-precision and non-contact dynamic angular displacement measurement with dual-Laser Doppler Vibrometers. Scientific Reports, 8(1), 9094. doi:10.1038/s41598-018-27410-4.

Wang, K., Chen, Q., Jiang, C., Chen, Z., Lou, J., Lu, M., ... & Guo, W. (2023). Characterization of thermo-optically tuned multi-channel interference widely tunable semiconductor laser for quasi-continuous tuning. Journal of Lightwave Technology, 41(10), 3084-3093. doi:10.1109/JLT.2023.3241892.

Duan, Y., Liang, L., Tong, X., Luo, B., & Cheng, B. (2023). Application of pipeline leakage detection based on distributed optical fiber acoustic sensor system and convolutional neural network. Journal of Physics D: Applied Physics, 57(10), 105102. doi:10.1088/1361-6463/ad1144.

Wu, J., Chen, Y., Guo, R., & Chen, J. (2024). A dynamic turbine tip clearance measurement method based on laser self-mixing interferometric ranging considering Doppler effect. Measurement Science and Technology, 35(11), 115012. doi:10.1088/1361-6501/ad6a75.

Chen, H., Zhong, Z., Ge, S., Zhu, D., Lin, Y., Kong, X., ... & Huang, W. (2024). Robust Time-Domain-Based Spectral Processing Method for Laser Self-Mixing Vibration Measurement. IEEE Transactions on Instrumentation Measurement, 73, 3449962. doi:10.1109/TIM.2024.3449962.

Lin, F., Ali, M., Tan, Y., Su, Z., & Wong, H. (2023). Laser offline measurement method based on self-mixing interference for thin-wall fused deposition modelling component. Journal of Manufacturing Processes, 102, 131-142. doi:10.1016/j.jmapro.2023.07.041.

Zhao, S., Xin, H., Wu, S., Sun, Y., & Hu, B. (2024). Attenuation of Ultraviolet Radiation by Aerosols and Clouds in Beijing Area in 2005–2020. Atmosphere, 15(3), 311. doi:10.3390/atmos15030311.

Shan, T., Yuan, R., He, N., & Cheng, J. (2023). Non-line-of-sight ultraviolet transmission coverage in non-precipitating, foggy, and rainy weather. Optics Express, 31(23), 37703-37721. doi:10.1364/OE.502380.

Wang, P., Xiang, X., Dong, P., & Liang, Y. (2024). Maximum Likelihood Sequence Estimation Optimum Receiver Design with Channel Identification Based on Zero Distribution. Electronics, 13(19), 3877. doi:10.1109/COMST.2023.3339371.

Mustafa, R., Sarkar, N. I., Mohaghegh, M., & Pervez, S. (2024). A Cross-Layer Secure and Energy-Efficient Framework for the Internet of Things: A Comprehensive Survey. Sensors (Switzerland), 24(22), 7209. doi:10.3390/s24227209.

Liu, X., Lu, H., Zhu, Y., Ma, J., Hao, R., Chen, D., & Wang, J. (2024). Experimental study on the transmission performance of an ultraviolet and visible light communication system under an artificial fog channel. Optics Express, 32(17), 30622-30631. doi:10.1364/OE.525762.

Kannapiran, S., Chandran, S., Jayasuriya, S., & Berman, S. (2024). PathFinder: Attention-Driven Dynamic Non-Line-of-Sight Tracking with a Mobile Robot. arXiv preprint, arXiv:2404.05024. doi:10.48550/arXiv.2404.05024.

Zhao, Y., Zhang, B., & Han, L. (2020). Laser self-mixing interference displacement measurement based on VMD and phase unwrapping. Optics Communications, 456, 124588 2020. doi:10.1016/j.optcom.2019.124588.

Sun, W., Yang, Z., Feng, G., Chen, Z., Chang, Q., Hai, L., & Guo, Z. (2023). A Novel Method for Detecting Fe2+ at a Micromolar Concentration Based on Multiple Self-Mixing Interference Using a Fiber Laser. Sensors, 23(5), 2838 2023. doi:10.3390/s23052838.

Liu, H., You, Y., Li, S., He, D., Sun, J., Wang, J., & Hou, D. (2023). Denoising of Laser Self-Mixing Interference by Improved Wavelet Threshold for High Performance of Displacement Reconstruction. Photonics, 10(8), 943. doi:10.3390/photonics10080943.

Wang, X., Zhong, Z., Chen, H., Zhu, D., Zheng, T., & Huang, W. (2023). High-Precision Laser Self-Mixing Displacement Sensor Based on Orthogonal Signal Phase Multiplication Technique. Photonics, 10(5), 575. doi:10.3390/photonics10050575.

Yu, L., Yang, Y., Liu, B., Tang, P., Ji, H., Wang, J., & Tan, T. (2023). Laser Self-Mixing Interference: Optical Fiber Coil Sensors for Acoustic Emission Detection. Photonics, 10(9), 958. doi:10.3390/photonics10090958.

Shen, E., Duan, S., Guo, S., & Yang, W. (2024). Object Localization and Sensing in Non-Line-of-Sight Using RFID Tag Matrices. Electronics (Switzerland), 13(2), 341 2024. doi:10.3390/electronics13020341.

Liu, B., Wang, B., Ruan, Y., Yu, Y., Xi, J., Ji, H., & Tang, P. (2024). Time-multiplexed laser self-mixing sensor for measurement of multiple material elastic moduli. Optics and Laser Technology, 176, 110963 2024. doi:10.1016/j.optlastec.2024.110963.

Zhao, Y., & Zhang, H. (2021). Angle measurement method based on speckle affected laser self-mixing interference signal. Optics Communications, 482, 126569 2021. doi:10.1016/j.optcom.2020.126569.

Zhao, T., Li, Y., & Yuan, L. (2019). Research on relay selection of armored formations wireless UV covert communication. Opto-Electronic Engineering, 46(5), 180448. doi:10.12086/oee.2019.180448.

Yue, K. (2024). Application of EEUC-based inter aircraft ultraviolet communication network algorithm in energy consumption optimization of drone swarm. Energy Informatics, 7(1), 27. doi:10.1186/s42162-024-00331-5.

Zhao, T., Cheng, M., Lyu, X., Zhang, H., & Wang, L. (2024). An unequal clustering energy consumption balancing routing algorithm of UAV swarm based on ultraviolet secret communication. Wireless Personal Communications, 137(1), 221-235. doi:10.1007/s11277-024-11394-8.


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DOI: 10.28991/HIJ-2024-05-04-012

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