{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T04:36:25Z","timestamp":1778301385987,"version":"3.51.4"},"reference-count":32,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,18]],"date-time":"2022-10-18T00:00:00Z","timestamp":1666051200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51975116"],"award-info":[{"award-number":["51975116"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["21ZR1402900"],"award-info":[{"award-number":["21ZR1402900"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007219","name":"Natural Science Foundation of Shanghai","doi-asserted-by":"publisher","award":["51975116"],"award-info":[{"award-number":["51975116"]}],"id":[{"id":"10.13039\/100007219","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007219","name":"Natural Science Foundation of Shanghai","doi-asserted-by":"publisher","award":["21ZR1402900"],"award-info":[{"award-number":["21ZR1402900"]}],"id":[{"id":"10.13039\/100007219","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Visual recognition and localization of underwater optical beacons is an important step in autonomous underwater vehicle (AUV) docking. The main issues that restrict the use of underwater monocular vision range are the attenuation of light in water, the mirror image between the water surface and the light source, and the small size of the optical beacon. In this study, a fast monocular camera localization method for small 4-light beacons is proposed. A YOLO V5 (You Only Look Once) model with coordinated attention (CA) mechanisms is constructed. Compared with the original model and the model with convolutional block attention mechanisms (CBAM), and our model improves the prediction accuracy to 96.1% and the recall to 95.1%. A sub-pixel light source centroid localization method combining super-resolution generative adversarial networks (SRGAN) image enhancement and Zernike moments is proposed. The detection range of small optical beacons is increased from 7 m to 10 m. In the laboratory self-made pool and anechoic pool experiments, the average relative distance error of our method is 1.04 percent, and the average detection speed is 0.088 s (11.36 FPS). This study offers a solution for the long-distance fast and accurate positioning of underwater small optical beacons due to their fast recognition, accurate ranging, and wide detection range characteristics.<\/jats:p>","DOI":"10.3390\/s22207940","type":"journal-article","created":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T00:58:51Z","timestamp":1666141131000},"page":"7940","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Fast Underwater Optical Beacon Finding and High Accuracy Visual Ranging Method Based on Deep Learning"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5886-2568","authenticated-orcid":false,"given":"Bo","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Science, Donghua University, Shanghai 201620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8240-7581","authenticated-orcid":false,"given":"Ping","family":"Zhong","sequence":"additional","affiliation":[{"name":"College of Science, Donghua University, Shanghai 201620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4435-6167","authenticated-orcid":false,"given":"Fu","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Science, Donghua University, Shanghai 201620, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianhua","family":"Zhou","sequence":"additional","affiliation":[{"name":"Key Laboratory of Space Laser Communication and Detection Technology, Shanghai Institute of Optics and Fine Mechanics, Chinses Academy of Sciences, Shanghai 201800, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingfei","family":"Shen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Space Laser Communication and Detection Technology, Shanghai Institute of Optics and Fine Mechanics, Chinses Academy of Sciences, Shanghai 201800, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/s10015-021-00720-z","article-title":"Stereo-vision-based AUV navigation system for resetting the inertial navigation system error","volume":"27","author":"Hsu","year":"2022","journal-title":"Artif. Life Robot."},{"key":"ref_2","unstructured":"Guo, Y., Bian, C., Zhang, Y., and Gao, J. (2021, January 24\u201326). An EPnP Based Extended Kalman Filtering Approach forDocking Pose Estimation ofAUVs. Proceedings of the International Conference on Autonomous Unmanned Systems (ICAUS 2021), Changsha, China."},{"key":"ref_3","unstructured":"Dong, H., Wu, Z., Wang, J., Chen, D., Tan, M., and Yu, J. (2022). Implementation of Autonomous Docking and Charging for a Supporting Robotic Fish. IEEE Trans. Ind. Electron., 1\u20139."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Bosch, J., Gracias, N., Ridao, P., Istenic, K., and Ribas, D. (2016). Close-Range Tracking of Underwater Vehicles Using Light Beacons. Sensors, 16.","DOI":"10.3390\/s16040429"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1016\/j.margeo.2014.03.012","article-title":"Autonomous Underwater Vehicles (AUVs): Their past, present and future contributions to the advancement of marine geoscience","volume":"352","author":"Wynn","year":"2014","journal-title":"Mar. Geol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.robot.2014.10.006","article-title":"Autonomous inspection of underwater structures","volume":"67","author":"Jacobi","year":"2015","journal-title":"Robot. Auton. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1531","DOI":"10.1016\/j.conengprac.2003.11.008","article-title":"Adaptive tuning of a Kalman filter via fuzzy logic for an intelligent AUV navigation system","volume":"12","author":"Loebis","year":"2004","journal-title":"Control Eng. Pract."},{"key":"ref_8","unstructured":"Sans-Muntadas, A., Brekke, E.F., Hegrenaes, O., and Pettersen, K.Y. (2015, January 24\u201326). Navigation and Probability Assessment for Successful AUV Docking Using USBL. Proceedings of the 10th IFAC Conference on Manoeuvring and Control of Marine Craft, Copenhagen, Denmark."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1541","DOI":"10.1016\/j.conengprac.2003.12.010","article-title":"Preliminary field experience with the DVLNAV integrated navigation system for oceanographic submersibles","volume":"12","author":"Kinsey","year":"2004","journal-title":"Control Eng. Pract."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.oceaneng.2008.08.007","article-title":"Underwater autonomous manipulation for intervention missions AUVs","volume":"36","author":"Marani","year":"2009","journal-title":"Ocean. Eng."},{"key":"ref_11","unstructured":"Nicosevici, T., Garcia, R., Carreras, M., Villanueva, M., and IEEE (2004, January 9\u201312). A review of sensor fusion techniques for underwater vehicle navigation. Proceedings of the Oceans \u201904 MTS\/IEEE Techno-Ocean \u201904 Conference, Kobe, Japan."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1551","DOI":"10.1016\/j.conengprac.2003.12.005","article-title":"Navigation of an AUV for investigation of underwater structures","volume":"12","author":"Kondo","year":"2004","journal-title":"Control Eng. Pract."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1825","DOI":"10.3390\/s150101825","article-title":"Inertial Sensor Self-Calibration in a Visually-Aided Navigation Approach for a Micro-AUV","volume":"15","author":"Beltran","year":"2015","journal-title":"Sensors"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.oceaneng.2015.10.015","article-title":"AUV docking experiments based on vision positioning using two cameras","volume":"110","author":"Li","year":"2015","journal-title":"Ocean Eng."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zhong, L., Li, D., Lin, M., Lin, R., and Yang, C. (2019). A Fast Binocular Localisation Method for AUV Docking. Sensors, 19.","DOI":"10.3390\/s19071735"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2720","DOI":"10.1109\/ACCESS.2018.2885537","article-title":"Detection and Pose Estimation for Short-Range Vision-Based Underwater Docking","volume":"7","author":"Liu","year":"2019","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"10082","DOI":"10.1109\/JSEN.2020.3042306","article-title":"Two AUVs Guidance Method for Self-Reconfiguration Mission Based on Monocular Vision","volume":"21","author":"Ren","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Venkatesh Alla, D.N., Bala Naga Jyothi, V., Venkataraman, H., and Ramadass, G.A. (2022, January 21\u201324). Vision-based Deep Learning algorithm for Underwater Object Detection and Tracking. Proceedings of the OCEANS 2022-Chennai, Chennai, India.","DOI":"10.1109\/OCEANSChennai45887.2022.9775438"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1232","DOI":"10.3389\/fenrg.2022.960278","article-title":"Autonomous underwater vehicle docking system for energy and data transmission in cabled ocean observatory networks","volume":"10","author":"Sun","year":"2022","journal-title":"Front. Energy Res."},{"key":"ref_20","unstructured":"Jocher, G. (2021, October 12). YOLOv5 Release v6.0. Available online: https:\/\/github.com\/ultralytics\/yolov5\/tree\/v6.0."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., and Kweon, I.S. (2018, January 8\u201314). CBAM: Convolutional Block Attention Module. Proceedings of the 15th European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Hou, Q., Zhou, D., Feng, J., and Ieee Comp, S.O.C. (2021, January 19\u201325). Coordinate Attention for Efficient Mobile Network Design. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Electr Network.","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ledig, C., Theis, L., Husz\u00e1r, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A., Tejani, A., Totz, J., and Wang, Z. (2017, January 22\u201325). Photo-realistic single image super-resolution using a generative adversarial network. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1109\/34.55109","article-title":"Invariant image recognition by Zernike moments","volume":"12","author":"Khotanzad","year":"1990","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/34.862199","article-title":"Fast and globally convergent pose estimation from video images","volume":"22","author":"Lu","year":"2000","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Kuang, Y., Sugimoto, S., Astrom, K., and Okutomi, M. (2013, January 1\u20138). Revisiting the pnp problem: A fast, general and optimal solution. Proceedings of the IEEE International Conference on Computer Vision, Sydney, Australia.","DOI":"10.1109\/ICCV.2013.291"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.patrec.2018.02.028","article-title":"A simple, robust and fast method for the perspective-n-point problem","volume":"108","author":"Wang","year":"2018","journal-title":"Pattern Recognit. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1016\/j.oceaneng.2009.03.007","article-title":"Paving the way for a future underwater omni-directional wireless optical communication systems","volume":"36","author":"Baiden","year":"2009","journal-title":"Ocean Eng."},{"key":"ref_30","unstructured":"Bochkovskiy, A., Wang, C.-Y., and Liao, H.-Y.M. (2020). Yolov4: Optimal speed and accuracy of object detection. arXiv."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., and Batra, D. (2017, January 22-29). Grad-cam: Visual explanations from deep networks via gradient-based localization. Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"72567","DOI":"10.1109\/ACCESS.2019.2917791","article-title":"Autonomous Underwater Vehicle Vision Guided Docking Experiments Based on L-Shaped Light Array","volume":"7","author":"Yan","year":"2019","journal-title":"IEEE Access"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/20\/7940\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:56:38Z","timestamp":1760144198000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/20\/7940"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,18]]},"references-count":32,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["s22207940"],"URL":"https:\/\/doi.org\/10.3390\/s22207940","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,18]]}}}