{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T23:07:50Z","timestamp":1773788870981,"version":"3.50.1"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,4,21]],"date-time":"2022-04-21T00:00:00Z","timestamp":1650499200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,4,21]],"date-time":"2022-04-21T00:00:00Z","timestamp":1650499200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["EURASIP J. Adv. Signal Process."],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Autonomous underwater vehicles (AUVs) are essential assets for ocean exploration requiring reliable underwater positioning technology. Aiming to improve the latter technology in a low SNR and reverberation environment, the Chan\u2013Taylor hybrid positioning algorithm establishes a long-baseline system (LBL) based on the time difference of arrival (TDOA) by reducing the number of sensors required while preserving the positioning accuracy. However, the traditional LBL algorithm\u2019s accuracy is reduced due to the critical time delay estimation under such environmental conditions. Hence, this paper suggests a new LBL positioning technology relying on an empirical mode decomposition (EMD) to construct a filter function combined with the maximum likelihood (ML) estimation method. MATLAB\/Simulink is applied to establish the simulation environment of LBL localization system, simulating the AUV motion under 5\u201330\u00a0dB SNR. This paper analyzes the accuracy of TDOA by generalizing the cross-correlation method (GCC), phase transform (PHAT), ML, and EMD\u2013ML. Based on the TDOA value obtained by the EMD\u2013ML filtering algorithm, the positioning errors of the Chan\u2013Taylor hybrid positioning algorithm and the Chan algorithm are compared. The results show that comparative synthetic evaluations against the traditional GCC demonstrate that the proposed method has a higher time delay estimation accuracy within a reverberation environment with SNR less than 15\u00a0dB. The Chan\u2013Taylor hybrid positioning algorithm limits the errors of the CHAN algorithm and improves the overall positioning system accuracy.\n<\/jats:p>","DOI":"10.1186\/s13634-022-00869-0","type":"journal-article","created":{"date-parts":[[2022,4,21]],"date-time":"2022-04-21T08:05:07Z","timestamp":1650528307000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["An LBL positioning algorithm based on an EMD\u2013ML hybrid method"],"prefix":"10.1186","volume":"2022","author":[{"given":"Huibao","family":"Yang","sequence":"first","affiliation":[]},{"given":"Xiujing","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Hongwu","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Banshuai","family":"Li","sequence":"additional","affiliation":[]},{"given":"Bo","family":"Xiao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,4,21]]},"reference":[{"key":"869_CR1","doi-asserted-by":"crossref","unstructured":"N.H. Tran, N.N.T. Pham, Design adaptive controller and guidance system of an unmanned surface vehicle for environmental monitoring applications. Paper presented at international conference on green technology and sustainable development, Ho Chi Minh University of Technology, Vnuhcm, Vietnam, 1 Nov 2018","DOI":"10.1109\/GTSD.2018.8595687"},{"key":"869_CR2","doi-asserted-by":"crossref","unstructured":"S. Zhou, X.U. Yao, H. Wang, X.U. Chunguang, Time delay estimation via third-order cumulant. Paper presented at 2013 far east forum on nondestructive evaluation\/testing: new technology and application, Jinan, China, 17\u201320 June 2013","DOI":"10.1109\/FENDT.2013.6635533"},{"key":"869_CR3","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1186\/s10033-020-00441-7","volume":"33","author":"MW Lin","year":"2020","unstructured":"M.W. Lin, C.J. Yang, Ocean observation technologies: a review. Chin. J. Mech. Eng. 33, 25\u201342 (2020)","journal-title":"Chin. J. Mech. Eng."},{"key":"869_CR4","first-page":"1","volume":"195","author":"H Huang","year":"2020","unstructured":"H. Huang, Q.R. Tang, J.Y. Li, W.L. Zhang, X. Bao, H.T. Zhu, G. Wang, A review on underwater autonomous environmental perception and target grasp, the challenge of robotic organism capture. Ocean Eng. 195, 1\u201311 (2020)","journal-title":"Ocean Eng."},{"key":"869_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.apor.2019.06.002","volume":"90","author":"YH Wu","year":"2019","unstructured":"Y.H. Wu, X.X. Ta, R.C. Xiao, Y.G. Wei, D. An, D.L. Li, Survey of underwater robot positioning navigation. Appl. Ocean Res. 90, 1\u201315 (2019)","journal-title":"Appl. Ocean Res."},{"key":"869_CR6","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.apacoust.2016.04.009","volume":"111","author":"J Zhang","year":"2016","unstructured":"J. Zhang, Y. Han, C. Zheng, D. Sun, Underwater target localization using long baseline positioning system. Appl. Acoust. 111, 129\u2013134 (2016)","journal-title":"Appl. Acoust."},{"key":"869_CR7","doi-asserted-by":"publisher","first-page":"1837","DOI":"10.1080\/00207721.2014.955070","volume":"47","author":"P Batista","year":"2016","unstructured":"P. Batista, C. Silvestre, P. Oliveira, Tightly coupled long baseline\/ultra-short baseline integrated navigation system. Int. J. Syst. Sci. 47, 1837\u20131855 (2016)","journal-title":"Int. J. Syst. Sci."},{"key":"869_CR8","doi-asserted-by":"publisher","first-page":"1673","DOI":"10.1007\/s11036-020-01577-5","volume":"25","author":"K Hao","year":"2020","unstructured":"K. Hao, K. Yu, Z. Gong, X. Du, Y. Liu, L. Zhao, An enhanced AUV-aided TDOA localization algorithm for underwater acoustic sensor networks. Mob. Netw. Appl. 25, 1673\u20131682 (2020)","journal-title":"Mob. Netw. Appl."},{"key":"869_CR9","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1109\/TASSP.1976.1162830","volume":"24","author":"C Knapp","year":"1976","unstructured":"C. Knapp, G. Carter, Thegeneralized correlation method for estimation of time delay. IEEE Trans. Acoust. Speech Signal Process. 24, 320\u2013327 (1976)","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"key":"869_CR10","doi-asserted-by":"crossref","unstructured":"M. Liang, L. Xi-Hai, Z. Wan-Gang, L. Dai-Zhi, The generalized cross-correlation method for time delay estimation of infrasound signal. Paper presented at 2015 fifth international conference on instrumentation and measurement, computer, communication and control (IMCCC), Qinhuangdao, China, 18\u201320 Sept 2015","DOI":"10.1109\/IMCCC.2015.283"},{"key":"869_CR11","first-page":"11","volume":"8","author":"D Sanjeev","year":"2010","unstructured":"D. Sanjeev, D.S. Arya, D. Sahu, Comparison of time-delay estimation techniques in acoustic environment. Int. J. Comput. Appl. 8, 11\u201317 (2010)","journal-title":"Int. J. Comput. Appl."},{"key":"869_CR12","first-page":"237","volume":"44","author":"B Patel","year":"2015","unstructured":"B. Patel, S.R.K. Vadali, S. Nandy, S.N. Shome, On methods to improve time delay estimation for underwater acoustic source localization. Indian J. Geo-Mar. Sci. 44, 237\u2013244 (2015)","journal-title":"Indian J. Geo-Mar. Sci."},{"key":"869_CR13","first-page":"3268","volume":"24","author":"MS Hosseini","year":"2017","unstructured":"M.S. Hosseini, A.H. Rezaie, Y. Zanjireh, Time difference of arrival estimation of sound source using cross correlation and modified maximum likelihood weighting function. Sci. Iran. 24, 3268\u20133279 (2017)","journal-title":"Sci. Iran."},{"key":"869_CR14","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1093\/biomet\/60.2.241","volume":"60","author":"EJ Hannan","year":"1973","unstructured":"E.J. Hannan, P.J. Thomson, Estimating group delay. Biometrika 60, 241\u2013253 (1973)","journal-title":"Biometrika"},{"key":"869_CR15","doi-asserted-by":"publisher","first-page":"655","DOI":"10.1016\/j.measurement.2019.01.096","volume":"137","author":"BMR Bharathi","year":"2019","unstructured":"B.M.R. Bharathi, A.R. Mohanty, Time delay estimation in reverberant and low SNR environment by EMD based maximum likelihood method. Measurement 137, 655\u2013663 (2019)","journal-title":"Measurement"},{"key":"869_CR16","doi-asserted-by":"publisher","DOI":"10.3390\/app10041256","author":"J Gonzalez-Garcia","year":"2020","unstructured":"J. Gonzalez-Garcia, A. Gomez-Espinosa, E. Cuan-Urquizo, L.G. Garcia-Valdovinos, T. Salgado-Jimenez, J.A.E. Cabello, Autonomous underwater vehicles: localization, navigation, and communication for collaborative missions. Appl. Sci. Basel (2020). https:\/\/doi.org\/10.3390\/app10041256","journal-title":"Appl. Sci. Basel"},{"key":"869_CR17","doi-asserted-by":"publisher","DOI":"10.3390\/s16010042","author":"T Zhang","year":"2016","unstructured":"T. Zhang, L.P. Chen, Y. Li, AUV underwater positioning algorithm based on interactive assistance of SINS and LBL. Sensors (2016). https:\/\/doi.org\/10.3390\/s16010042","journal-title":"Sensors"},{"key":"869_CR18","first-page":"72","volume":"34","author":"J Ning","year":"2014","unstructured":"J. Ning, W.U. Yongting, D. Sun, The development of LBL acoustic positioning system and its application. Hydrogr. Surv. Charting 34, 72\u201375 (2014)","journal-title":"Hydrogr. Surv. Charting"},{"key":"869_CR19","doi-asserted-by":"crossref","unstructured":"Y.S.M. Simamora, H.A. Tjokronegoro, E. Leksono, I.S. Brodjonegoro, Compensation of INS errors based on LBL references in a quadratic sound-speed-profile. Paper presented at 2020 6th information technology international seminar, Surabaya, Indonesia, 15 Oct 2020","DOI":"10.1109\/ITIS50118.2020.9321079"},{"key":"869_CR20","doi-asserted-by":"publisher","first-page":"58541","DOI":"10.1109\/ACCESS.2019.2914924","volume":"7","author":"YG Yue","year":"2019","unstructured":"Y.G. Yue, L. Cao, J. Hu, S.T. Cai, B. Hang, H. Wu, A novel hybrid location algorithm based on chaotic particle swarm optimization for mobile position estimation. IEEE Access 7, 58541\u201358552 (2019)","journal-title":"IEEE Access"},{"key":"869_CR21","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/7828050","author":"HJ Wang","year":"2020","unstructured":"H.J. Wang, Y. Wang, C. Li, J. Li, Q. Li, X.C. Ban, Adaptive weight update algorithm for target tracking of UUV based on improved Gaussian mixture cubature kalman filter. Complexity (2020). https:\/\/doi.org\/10.1155\/2020\/7828050","journal-title":"Complexity"},{"key":"869_CR22","doi-asserted-by":"publisher","first-page":"1905","DOI":"10.1109\/78.301830","volume":"42","author":"YT Chan","year":"1994","unstructured":"Y.T. Chan, K.C. Ho, A simple and efficient estimator for hyperbolic location. IEEE Trans. Signal Process. 42, 1905\u20131915 (1994)","journal-title":"IEEE Trans. Signal Process."},{"key":"869_CR23","first-page":"684","volume":"6","author":"L Li","year":"2002","unstructured":"L. Li, P. Deng, L. Liu, Taylor series expansion method and its performance analysis. J. Southwest Jiaotong Univ. 6, 684\u2013688 (2002)","journal-title":"J. Southwest Jiaotong Univ."},{"key":"869_CR24","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1093\/biomet\/60.2.217","volume":"60","author":"P Bloomfield","year":"1973","unstructured":"P. Bloomfield, Estimating group delay. Biometrika 60, 241\u2013253 (1973)","journal-title":"Biometrika"},{"key":"869_CR25","unstructured":"S. Bedard, B. Champagne, Effects of room reverberation on time-delay estimation performance, in IEEE International Conference on Acoustics, Speech and Signal Processing, 19\u201322 April 1994"},{"key":"869_CR26","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1098\/rspa.1998.0193","volume":"454","author":"NE Huang","year":"1998","unstructured":"N.E. Huang, Z. Shen, S.R. Long, M.C. Wu, H.H. Shih, Q. Zheng, N.C. Yen, C.C. Tung, H.H. Liu, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc. Math. Phys. Eng. Sci. 454, 903\u2013995 (1998)","journal-title":"Proc. Math. Phys. Eng. Sci."},{"key":"869_CR27","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1016\/B0-12-227410-5\/00010-7","volume-title":"Encyclopedia of Physical Science and Technology (Third Edition)","author":"WA Kuperman","year":"2003","unstructured":"W.A. Kuperman, in Encyclopedia of Physical Science and Technology (Third Edition). ed. by R.A. Meyers (Academic Press, New York, 2003), p. 317"}],"container-title":["EURASIP Journal on Advances in Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13634-022-00869-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13634-022-00869-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13634-022-00869-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,21]],"date-time":"2022-04-21T20:10:31Z","timestamp":1650571831000},"score":1,"resource":{"primary":{"URL":"https:\/\/asp-eurasipjournals.springeropen.com\/articles\/10.1186\/s13634-022-00869-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,21]]},"references-count":27,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["869"],"URL":"https:\/\/doi.org\/10.1186\/s13634-022-00869-0","relation":{},"ISSN":["1687-6180"],"issn-type":[{"value":"1687-6180","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,21]]},"assertion":[{"value":"8 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 April 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 April 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethic approval and consent to participate"}},{"value":"The picture materials quoted in this article have no copyright requirements, and the source has been indicated.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"38"}}