Although advances in research into autonomous underwater vehicles (AUVs) have been made to
extend their working depth and endurance, underwater experiments and missions remain to be restricted by the
positioning performance of AUVs. With the Global Navigation Satellite System (GNSS) precluded due to the
rapid attenuation of radio signals in underwater environments, acoustic positioning methods serve as an effective
substitution. A long-range continuous and precise positioning solution for AUVs in deep ocean is proposed in
this study, relying on acoustic signals from beacons at the same depth and aided by onboard inertial sensors. A
signal system is investigated to provide time of arrival (TOA) estimation in a resolution of milliseconds. Without
pre-knowledge or local measurement of the accurate sound speed, an AUV is enabled to continuously locate its
horizontal position based on rough ranges estimated by an iterative least square (ILS) based algorithm. For
better accuracy and robustness, range deviations are compensated with a reference point of known position and
outliers in the trajectory are eliminated by an implementation of the extended Kalman filter (EKF) coupled with
the state-acceptance filter. The solution is evaluated in simulation experiments with environmental information
measured on the spot, providing an average position error from ground truth below 10 m with a standard deviation
below 5 m.
[1] YAN J, MENG Y, LUO X Y, et al. To hide private position information in localization for Internet of underwater things [J]. IEEE Internet of Things Journal, 2021, 8(18): 14338-14354.
[2] COUTINHO R W L, BOUKERCHE A, VIEIRA L F M, et al. Geographic and opportunistic routing for underwater sensor networks [J]. IEEE Transactions on Computers, 2016, 65(2): 548-561.
[3] CHENG X Z, SHU H N, LIANG Q L, et al. Silent positioning in underwater acoustic sensor networks [J]. IEEE Transactions on Vehicular Technology, 2008, 57(3): 1756-1766.
[4] YAN J, GONG Y D, CHEN C L, et al. AUV-aided localization for Internet of underwater things: A reinforcement-learning-based method [J]. IEEE Internet of Things Journal, 2020, 7(10): 9728-9746.
[5] YAN J, MENG Y, YANG X, et al. Privacy-preserving localization for underwater sensor networks via deep reinforcement learning [J]. IEEE Transactions on Information Forensics and Security, 2021, 16: 18801895.
[6] YAN J, GUO D B, LUO X Y, et al. AUV-aided localization for underwater acoustic sensor networks with current field estimation [J]. IEEE Transactions on Vehicular Technology, 2020, 69(8): 8855-8870.
[7] LEONARD J J, BAHR A. Autonomous underwater vehicle navigation [M]//Dhanak M R, Xiros N I. Springer Handbook of Ocean Engineering. Cham: Springer, 2016: 341-358.
[8] PAULL L, SAEEDI S, SETO M, et al. AUV navigation and localization: A review [J]. IEEE Journal of Oceanic Engineering, 2014, 39(1): 131-149.
[9] WU Y H, TA X X, XIAO R C, et al. Survey of underwater robot positioning navigation [J]. Applied Ocean Research, 2019, 90: 101845.
[10] MIKHALEVSKY P N, SPERRY B J, WOOLFE K F, et al. Deep Ocean long range underwater navigation [J]. The Journal of the Acoustical Society of America, 2020, 147(4): 2365-2382.
[11] ROSSBY T, DORSON D, FONTAINE J. The RAFOS system [J]. Journal of Atmospheric and Oceanic Technology, 1986, 3(4): 672-679.
[12] DUDA T F, MOROZOV A K, HOWE B M, et al. Evaluation of a long-range joint acoustic navigation/thermometry system [C]//OCEANS 2006. Boston, MA: IEEE, 2006: 1-6.
[13] WEBSTER S E, FREITAG L E, LEE C M, et al. Towards real-time under-ice acoustic navigation at mesoscale ranges [C]//2015 IEEE International Conference on Robotics and Automation. Seattle, W A: IEEE, 2015: 537-544.
[14] VAN UFFELENLJ , HOWE B M , NOSAL E M , et al. Localization and subsurface position error estimation of gliders using broadband acoustic signals at long range [J]. IEEE Journal of Oceanic Engineering, 2016, 41(3): 501-508.
[15] SKARSOULIS E K, PIPERAKIS G S. Use of acoustic navigation signals for simultaneous localization and sound-speed estimation [J]. The Journal of the Acoustical Society of America, 2009, 125(3): 1384-1393.
[16] Ocean Acoustic Library. Acoustic toolbox [EB/OL]. (2018-07-06) [2020-11-04]. https://oalibacoustics.org/AcousticsToolbox/.
[17] MOROZS N, GORMA W, HENSON B T, et al. Channel modeling for underwater acoustic network simulation [J]. IEEE Access, 2020, 8: 136151-136175.
[18] MACKENZIE K V. Discussion of sea water sound-speed determinations [J]. The Journal of the Acoustical Society of America, 1981, 70(3): 801-806.
[19] MUNK W H. Sound channel in an exponentially stratified ocean, with application to SOFAR [J]. The Journal of the Acoustical Society of America, 1974, 55(2): 220-226.
[20] ETTER P C. Underwater acoustic modeling and simulation [M]. 5th ed. Florida: CRC press, 2018.
[21] STOJANOVIC M, PREISIG J. Underwater acoustic communication channels: Propagation models and statistical characterization [J]. IEEE Communications Magazine, 2009, 47(1): 84-89.
[22] THORP W H. Analytic description of the low-frequency attenuation coefficient [J]. The Journal of the Acoustical Society of America, 1967, 42(1): 270.
[23] STOJANOVIC M. On the relationship between capacity and distance in an underwater acoustic communication channel [J]. ACM SIGMOBILE Mobile Computing and Communications Review, 2007, 11(4): 34-43.
[24] BOYER T, GARCIA H, LOCARNINI R, et al. World Ocean Atlas 2018 [EB/OL]. (2020-09-07) [2020-1020]. https:// www.ncei.noaa.gov/ archive/ accession/ NCEI-WOA18.
[25] GEBCO Bathymetric Compilation Group 2020. The GEBCO 2020 grid [EB/OL]. (2020-06-12) [2020-1020]. https://www.gebco.net/ data and products/ gridded bathymetry data/ gebco 2020.
[26] BERSHAD S, WEISS M. Deck41 surficial seafloor sediment description database [EB/OL]. (2020-04-21) [2020-10-20]. https://doi.org/10.7289/V5VD6WCZ.
[27] TORRIERI D. Principles of spread-spectrum communication systems [M]. 4th ed. Boston, MA: Springer, 2018.
[28] AMAR A, AVRASHI G, STOJANOVIC M. Low complexity residual Doppler shift estimation for underwater acoustic multicarrier communication [J]. IEEE Transactions on Signal Processing, 2017, 65(8): 20632076.
[29] QU F Z, W ANG Z D, YANG L Q, et al. A journey toward modeling and resolving Doppler in underwater acoustic communications [J]. IEEE Communications Magazine, 2016, 54(2): 49-55.
[30] LI D D, JI D X, LIU J, et al. A multi-model EKF integrated navigation algorithm for deep water AUV [J]. International Journal of Advanced Robotic Systems, 2016, 13(1): 3.
[31] KEPPER J H, CLAUS B C, KINSEY J C. A navigation solution using a MEMS IMU, model-based dead-reckoning, and one-way-travel-time acoustic range measurements for autonomous underwater vehicles [J]. IEEE Journal of Oceanic Engineering, 2019, 44(3): 664-682.
[32] GREW AL M S, ANDREWS A P. Kalman filtering: Theory and practice with MATLAB [M]. 4th ed. New Jersey: John Wiley & Sons, 2014.
[33] TICHAVSKY P, MURAVCHIK C H, NEHORAI A. Posterior Cramer-Rao bounds for discrete-time nonlinear filtering [J]. IEEE Transactions on Signal Processing, 1998, 46(5): 1386-1396.
[34] WU M Y, BARMIN M P, ANDREW R K, et al. Deep water acoustic range estimation based on an ocean general circulation model: Application to PhilSea10 data [J]. The Journal of the Acoustical Society of America, 2019, 146(6): 4754-4773.
[35] ENGE P K. The global positioning system: Signals, measurements, and performance [M]. 2nd ed. Lincoln, MA: Ganga-Jamuna Press, 2012.
