{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T12:51:17Z","timestamp":1767703877573,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"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":["62101158","ZR2021QF004","61971156","ZR2019MF035","ZR2020MF141"],"award-info":[{"award-number":["62101158","ZR2021QF004","61971156","ZR2019MF035","ZR2020MF141"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Shandong Provincial Natural Science Foundation","award":["62101158","ZR2021QF004","61971156","ZR2019MF035","ZR2020MF141"],"award-info":[{"award-number":["62101158","ZR2021QF004","61971156","ZR2019MF035","ZR2020MF141"]}]},{"name":"the National Natural Science Foundation of China","award":["62101158","ZR2021QF004","61971156","ZR2019MF035","ZR2020MF141"],"award-info":[{"award-number":["62101158","ZR2021QF004","61971156","ZR2019MF035","ZR2020MF141"]}]},{"name":"the Shandong Provincial Natural Science Foundation","award":["62101158","ZR2021QF004","61971156","ZR2019MF035","ZR2020MF141"],"award-info":[{"award-number":["62101158","ZR2021QF004","61971156","ZR2019MF035","ZR2020MF141"]}]},{"name":"the Shandong Provincial Natural Science Foundationan","award":["62101158","ZR2021QF004","61971156","ZR2019MF035","ZR2020MF141"],"award-info":[{"award-number":["62101158","ZR2021QF004","61971156","ZR2019MF035","ZR2020MF141"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Singe-beacon localization technology can help Autonomous Underwater Vehicles (AUVs) to obtain precise positions by deploying only one beacon. It is considered as a promising way, benefiting from saving much time and labor compared with traditional Long-Baseline Localization (LBL). A typical single-beacon localization scheme contains two essential questions: the initial observability problem and long-endurance trajectory tracking problem. Aiming at these core problems, a comprehensive solution for single-beacon localization is described in this paper. An multi-hypothesis initial position discriminant method is proposed firstly, which helps to achieve accurate initial location based on observability analysis. Then, an Adaptive Network Fuzzy Inference System (ANFIS)-improved Extended Kalman Filter (EKF) method is proposed, in which single-beacon measuring information is fused with off-the-shelf sensors, including DVL, Compass, etc. ANFIS-EKF can help to improve trajectory tracking precisions by restraining the heavy loss of linearization in conventional EKF. Both simulation and field tests are conducted to verify the performance of the proposed algorithms.<\/jats:p>","DOI":"10.3390\/rs14205281","type":"journal-article","created":{"date-parts":[[2022,10,24]],"date-time":"2022-10-24T10:09:23Z","timestamp":1666606163000},"page":"5281","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["ANFIS-EKF-Based Single-Beacon Localization Algorithm for AUV"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8932-7960","authenticated-orcid":false,"given":"Wanlong","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Harbin Institute of Technology, Weihai 264200, China"}]},{"given":"Huifeng","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150009, China"}]},{"given":"Gongliang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Harbin Institute of Technology, Weihai 264200, China"}]},{"given":"Guoyao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Harbin Institute of Technology, Weihai 264200, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"27136","DOI":"10.1109\/JSEN.2021.3120663","article-title":"A Multi-Sensor Fusion Self-Localization System of a Miniature Underwater Robot in Structured and GPS-Denied Environments","volume":"21","author":"Xing","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_2","unstructured":"Scherbatyuk, A.P. (1995, January 9\u201312). The AUV positioning using ranges from one transponder LBL. Proceedings of the OCEANS, \u201895 MTS\/IEEE, San Diego, CA, USA."},{"key":"ref_3","unstructured":"Vaganay, J., Baccou, P., and Jouvencel, B. (2000, January 11\u201314). Homing by acoustic ranging to a single-beacon. Proceedings of the OCEANS 2000 MTS\/IEEE Conference and Exhibition, Providence, RI, USA."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.arcontrol.2016.09.007","article-title":"Sum of gaussian single-beacon range-only localization for AUV homing","volume":"42","author":"Vallicrosa","year":"2016","journal-title":"Annu. Rev. Control"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"650","DOI":"10.1016\/j.oceaneng.2017.07.025","article-title":"Underwater localization using single-beacon measurements: Observability analysis for a double integrator system","volume":"142","author":"Arrichiello","year":"2017","journal-title":"Ocean Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.1109\/JOE.2017.2754018","article-title":"Model and algorithm improvement on single-beacon underwater tracking","volume":"43","author":"Zhu","year":"2018","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Deng, Z.C., Yu, X., Qin, H.D., and Zhu, Z.B. (2018). Adaptive Kalman filter-based single-beacon underwater tracking with unknown effective sound velocity. Sensors, 18.","DOI":"10.3390\/s18124339"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1002\/rob.21746","article-title":"Closed-loop one-way-travel-time navigation using low-grade odometry for autonomous underwater vehicles","volume":"35","author":"Claus","year":"2018","journal-title":"J. Field Robot."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/j.neucom.2019.10.066","article-title":"An expectation-maximization based single-beacon underwater navigation method with unknown ESV","volume":"378","author":"Qin","year":"2019","journal-title":"Neurocomputing"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1109\/JOE.2018.2832878","article-title":"A navigation solution using a MEMS IMU, model-based dead-reckoning, and one-way-travel-time acoustic range measurements for autonomous underwater vehicles","volume":"44","author":"Kepper","year":"2019","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Sun, J., Hu, F., Jin, W.M., Wang, J., Wang, X., Luo, Y., Yu, J., and Zhang, A. (2020). Model-aided localization and navigation for underwater gliders using single-beacon travel-time differences. Sensors, 20.","DOI":"10.3390\/s20030893"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2515","DOI":"10.1016\/j.jfranklin.2021.01.010","article-title":"Globally exponentially stable single-beacon underwater navigation with unknown sound velocity estimation","volume":"358","author":"Yu","year":"2021","journal-title":"J. Frankl. Inst. Eng. Appl. Math."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1447","DOI":"10.1177\/0278364918802351","article-title":"Optimal path shape for range-only underwater target localization using a wave glider","volume":"37","author":"Masmitja","year":"2018","journal-title":"Int. J. Robot. Res."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Liu, H.M., Wang, Z.J., Zhao, S., and He, K. (2019). Accurate multiple ocean bottom seismometer positioning in shallow water using GNSS\/Acoustic Technique. Sensors, 19.","DOI":"10.3390\/s19061406"},{"key":"ref_15","first-page":"452","article-title":"Embracing localization inaccuracy with a single-beacon","volume":"10","author":"Rahman","year":"2019","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1268","DOI":"10.1109\/JOE.2019.2950954","article-title":"Underwater acoustical localization of the black box utilizing single autonomous underwater vehicle based on the second-order time difference of arrival","volume":"45","author":"Sun","year":"2020","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"107546","DOI":"10.1016\/j.apacoust.2020.107546","article-title":"Underwater asynchronous navigation using single-beacon based on the phase difference","volume":"172","author":"Sun","year":"2021","journal-title":"Appl. Acoust."},{"key":"ref_18","unstructured":"Larsen, M.B. (2000, January 11\u201314). Synthetic long baseline navigation of underwater vehicles. Proceedings of the OCEANS 2000 MTS\/IEEE Conference and Exhibition, Providence, RI, USA."},{"key":"ref_19","unstructured":"Lapointe C, E. (2006). Virtual Long Baseline (VLBL) Autonomous Underwater Vehicle Navigation Using a Single Transponder, Massachusetts Institute of Technology."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.apacoust.2016.10.001","article-title":"Linearized iterative method for determining effects of vessel attitude error on single-beacon localization","volume":"116","author":"Cao","year":"2017","journal-title":"Appl. Acoust."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Masmitja, I., Bouvet, P.J., Gomariz, S., Aguzzi, J., and del Rio, J. (2017, January 19\u201322). Underwater mobile target tracking with particle filter using an autonomous vehicle. Proceedings of the OCEANS 2017, Aberdeen, UK.","DOI":"10.1109\/OCEANSE.2017.8084692"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Shaukat, N., Ali, A., Javed, I.M., Moinuddin, M., and Orero, P. (2021). Multi-Sensor Fusion for Underwater Vehicle Localization by Augmentation of RBF Neural Network and Error-State Kalman Filter. Sensors, 21.","DOI":"10.3390\/s21041149"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ma, H., Mu, X., and He, B. (2021). Adaptive Navigation Algorithm with Deep Learning for Autonomous Underwater Vehicle. Sensors, 21.","DOI":"10.3390\/s21196406"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"85818","DOI":"10.1109\/ACCESS.2022.3198672","article-title":"Adaptive Step Size Learning with Applications to Velocity Aided Inertial Navigation System","volume":"10","author":"Or","year":"2022","journal-title":"IEEE Access"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1109\/21.256541","article-title":"ANFIS: Adaptive-network-based fuzzy inference system","volume":"23","author":"Jang","year":"1993","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Gharghan, S.K., Nordin, R., and Ismail, M. (2016). A wireless sensor network with soft computing localization techniques for track cycling applications. Sensors, 16.","DOI":"10.3390\/s16081043"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Duan, Y.B., Li, H.Z., Wu, S.Q., and Zhang, K. (2021). INS error estimation based on an ANFIS and its application in complex and covert surroundings. ISPRS Int. J. Geo-Inf., 10.","DOI":"10.3390\/ijgi10060388"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1109\/48.775299","article-title":"Observability of target tracking with range-only measurements","volume":"24","author":"Taek","year":"1999","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Kabir, M., and Kabir, M.M.J. (2021, January 27\u201329). Fuzzy membership function design: An adaptive neuro-fuzzy inference system (ANFIS) based approach. Proceedings of the 2021 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India.","DOI":"10.1109\/ICCCI50826.2021.9402633"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/20\/5281\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:00:35Z","timestamp":1760144435000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/20\/5281"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,21]]},"references-count":29,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["rs14205281"],"URL":"https:\/\/doi.org\/10.3390\/rs14205281","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,10,21]]}}}