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Error analysis of dead reckoning navigation system by considering uncertainties in an underwater vehicle's sensors

Published online by Cambridge University Press:  28 May 2024

Mohammad Reza Gharib Open the ORCID record for Mohammad Reza Gharib [Opens in a new window] ,
Mahmoud Ardekani Fard Open the ORCID record for Mahmoud Ardekani Fard [Opens in a new window]  and
Ali Koochi Open the ORCID record for Ali Koochi [Opens in a new window]
Mohammad Reza Gharib*
Affiliation:
Department of Mechanical Engineering, University of Torbat Heydarieh, Torbat Heydarieh, Iran
Mahmoud Ardekani Fard
Affiliation:
Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
Ali Koochi
Affiliation:
Department of Mechanical Engineering, University of Torbat Heydarieh, Torbat Heydarieh, Iran
*
*Corresponding author: Mohammad Reza Gharib; Email: m.gharib@torbath.ac.ir
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Abstract

In this paper, a complete introduction to the dead reckoning navigation technique is offered after a discussion of the many forms of navigation, and the benefits and drawbacks associated with each of those types of navigation. After that, the dead reckoning navigation solution is used as an option that is both low-cost and makes use of the sophisticated equations that are used by the system. Moreover, to achieve the highest level of accuracy in navigation, an investigation of navigation errors caused by dead reckoning is calculated. Employing the suggested dead reckoning navigation system, the final position of an underwater vehicle can be established with a high degree of accuracy by using experimental data (from sensors) and the uncertainties that are associated with the system. Finally, to illustrate the correctness of the dead reckoning navigation process, the system error analysis as uncertainty that was carried out using experimental data using the dead reckoning navigation technique is compared with GPS data.

Keywords

navigationdead reckoningerror analysissensor uncertainties
Type
Research Article
Information
The Journal of Navigation , First View , pp. 1 - 19
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Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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References

Aghili, F. and Salerno, A. (2013). Driftless 3-D attitude determination and positioning of mobile robots by integration of IMU with two RTK GPSs. IEEE/ASME Transactions on Mechatronics, 18(1), 21–31. doi:10.1109/TMECH.2011.2161485CrossRefGoogle Scholar
Amaral, R. R., Borges, J. A. and Gomes, H. M. (2022). Proportional topology optimization under reliability-based constraints. Journal of Applied and Computational Mechanics, 8(1), 319–330.Google Scholar
Bakhoum, E. G. (2010). Third-generation GPS: A low-maintenance, high-reliability future GPS system. International Journal of Communication Systems, 23(11), 1431–1442. doi:10.1002/dac.1132CrossRefGoogle Scholar
Bevly, D. M., Gebre-Egziabher, D. and Parkinson, B. (2006). Parametric error equations for dead reckoning navigators used in ground vehicle guidance and control. Navigation, 53(3), 135–147. doi:10.1002/j.2161-4296.2006.tb00379.xCrossRefGoogle Scholar
Brossard, M., Barrau, A. and Bonnabel, S. (2020). AI-IMU dead-reckoning. IEEE Transactions on Intelligent Vehicles, 5(4), 585–595. doi:10.1109/TIV.2020.2980758CrossRefGoogle Scholar
Campos, D. F., Löser, E. E. and Piovan, M. T. (2023). Self-damping of optical ground wire cables: A Bayesian approach. Journal of Applied and Computational Mechanics, 9(1), 205–216.Google Scholar
Carlson, C. R., Gerdes, J. C. and Powell, J. D. (2004). Error sources when land vehicle dead reckoning with differential wheelspeeds. Navigation, 51(1), 13–27. doi:10.1002/j.2161-4296.2004.tb00338.xCrossRefGoogle Scholar
Cestone, J. A. (1971). Precise underwater navigation. Journal of Navigation, 24(2), 154–164. doi:10.1017/s0373463300018634CrossRefGoogle Scholar
Chan, E. C. L. and Baciu, G. (2012). Introduction to Wireless Localization: With iPhone SDK Examples. New York: John Wiley & Sons.CrossRefGoogle Scholar
Claus, B. and Bachmayer, R. (2015). Terrain-aided navigation for an underwater glider. Journal of Field Robotics, 32(7), 935–951. doi:10.1002/rob.21563CrossRefGoogle Scholar
Cotter, C. H. (1978). Early dead reckoning navigation. Journal of Navigation, 31(1), 20–28. doi:10.1017/s0373463300038583CrossRefGoogle Scholar
Donovan, G. T. (2012). Position error correction for an autonomous underwater vehicle inertial navigation system (INS) using a particle filter. IEEE Journal of Oceanic Engineering, 37(3), 431–445. doi:10.1109/joe.2012.2190810CrossRefGoogle Scholar
Doostdar, P. and Keighobadi, J. (2012). Design and implementation of SMO for a nonlinear MIMO AHRS. Mechanical Systems and Signal Processing, 32, 94–115. doi:10.1016/j.ymssp.2012.02.007CrossRefGoogle Scholar
Fifield, L. W. J. (1979). Dead reckoning instrumentation. Journal of Navigation, 32(3), 309–319. doi:10.1017/s0373463300026187CrossRefGoogle Scholar
Filaretov, V. F., Zhirabok, A. N., Zyev, A. V., Protsenko, A. A., Tuphanov, I. E. and Scherbatyuk, A. F., (2015). Design and Investigation of Dead Reckoning System with Accommodation to Sensors Errors for Autonomous Underwater Vehicle. Presented at the OCEANS 2015 – MTS/IEEE, Washington. doi:10.23919/oceans.2015.7401832CrossRefGoogle Scholar
Gebre-Egziabher, D., Boyce, C. O. L., Powell, J. D. and Enge, P. E. R. (2003). An inexpensive DME-aided dead reckoning navigator. Navigation, 50(4), 247–263. doi:10.1002/j.2161-4296.2003.tb00333.xCrossRefGoogle Scholar
Gharib, M. R. and Moavenian, M. (2014). Synthesis of robust PID controller for controlling a single input single output system using quantitative feedback theory technique. Scientia Iranica. Transaction B, Mechanical Engineering, 21(6), 1861–1869.Google Scholar
Gharib, M. R., Heydari, A. and Salehi Kolahi, M. R. (2024). Modeling and analysis of static and dynamic behavior of marine towed cable-array system based on the vessel motion. Advances in Mechanical Engineering, 16(1), 1–13. doi:10.1177/16878132231220353CrossRefGoogle Scholar
Grewal, M. S., Weill, L. R. and Andrews, A. P. (2007). Global Positioning Systems, Inertial Navigation, and Integration. New York: John Wiley & Sons, Inc.CrossRefGoogle Scholar
Hacohen, S., Shoval, S. and Shvalb, N. (2017). Applying probability navigation function in dynamic uncertain environments. Robotics and Autonomous Systems, 87, 237–246. doi:10.1016/j.robot.2016.10.010CrossRefGoogle Scholar
Junratanasiri, S., Auephanwiriyakul, S. and Theera-Umpon, N. (2011). Navigation System of mobile Robot in an Uncertain Environment Using Type-2 Fuzzy Modelling. In 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), 27–30 June 2011, pp. 1171–1178. doi:10.1109/FUZZY.2011.6007722CrossRefGoogle Scholar
Kayton, M. and Fried, W. R. (1997). Avionics nAvigation Systems. New York: John Wiley & Sons.CrossRefGoogle Scholar
Kuang, J., Li, T. and Niu, X. (2022). Magnetometer bias insensitive magnetic field matching based on pedestrian dead reckoning for smartphone indoor positioning. IEEE Sensors Journal, 22(6), 4790–4799. doi:10.1109/JSEN.2021.3073397CrossRefGoogle Scholar
Kumar, V. and Das, S. R. (2004). Performance of dead reckoning-based location service for mobile ad hoc networks. Wireless Communications and Mobile Computing, 4(2), 189–202. doi:10.1002/wcm.163CrossRefGoogle Scholar
Leonard, J. J. and Bahr, A. (2016). Autonomous Underwater vehicle navigation. In: Xiros, D. (ed.). Springer HAndbook of Ocean Engineering, Berlin, Germany: Springer International Publishing, 341–358.CrossRefGoogle Scholar
McIntire, J. P., Webber, F. C., Nguyen, D. K., Li, Y., Foong, S., Schafer, K., Chue, W. Y., Ang, K., Vinande, E. T. and Miller, M. M. (2018). Leapfrogging: A technique for accurate long-distance ground navigation and positioning without GPS. Navigation, 65(1), 35–47. doi:10.1002/navi.220CrossRefGoogle Scholar
Noureldin, A., Karamat, T. B. and Georgy, J. (2012). Inertial navigation system. Fundamentals of Inertial Navigation, Satellite-Based Positioning and Their Integration, Berlin Heidelberg: Springer, 125–166.Google Scholar
Pankratz, F., Dippon, A., Coskun, T., and Klinker, G. (2013). User Awareness of Tracking Uncertainties in AR Navigation Scenarios. In 2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 1–4 October 2013, pp. 285–286. doi:10.1109/ISMAR.2013.6671807CrossRefGoogle Scholar
Ramesh, R., Jyothi, V. B. N., Vedachalam, N., Ramadass, G. A. and Atmanand, M. A. (2016). Development and performance validation of a navigation system for an underwater vehicle. Journal of Navigation, 69(5), 1097–1113. doi:10.1017/s0373463315001058CrossRefGoogle Scholar
Sabet, M. T., Daniali, H. R. M., Fathi, A. R. and Alizadeh, E. (2017). Experimental analysis of a low-cost dead reckoning navigation system for a land vehicle using a robust AHRS. Robotics and Autonomous Systems, 95, 37–51. doi:10.1016/j.robot.2017.05.010CrossRefGoogle Scholar
Saksvik, I. B., Alcocer, A. and Hassani, V. (2021). A Deep Learning Approach To Dead-Reckoning Navigation For Autonomous Underwater Vehicles With Limited Sensor Payloads. In OCEANS 2021: San Diego – Porto, 20–23 September 2021, pp. 1–9. doi:10.23919/OCEANS44145.2021.9706096CrossRefGoogle Scholar
Titterton, D. and Weston, J. (2004). Strapdown Inertial Navigation Technology. England & Wales and Scotland: Institution of Engineering and Technology.CrossRefGoogle Scholar
Tsakiri, M., Kealy, A. and Stewart, M. (1999). Urban canyon vehicle navigation with integrated GPS/GLONASS/DR systems. Navigation, 46(3), 161–174. doi:10.1002/j.2161-4296.1999.tb02404.xCrossRefGoogle Scholar
Wrigley, W. (1977). History of inertial navigation. Navigation, 24(1), 1–6. doi:10.1002/j.2161-4296.1977.tb01262.xCrossRefGoogle Scholar
Yan, S., Su, Y., Luo, X., Sun, A., Ji, Y. and Ghazali, K. H. B. (2023). Deep learning-based geomagnetic navigation method integrated with dead reckoning. Remote Sensing, 15(17), 4165.CrossRefGoogle Scholar
Zhai, C., Wang, M., Yang, Y. and Shen, K. (2020). Robust vision-aided inertial navigation system for protection against ego-motion uncertainty of unmanned ground vehicle. IEEE Transactions on Industrial Electronics, 68(12), 12462–12471.CrossRefGoogle Scholar
Zhao, H., Zhang, L., Qiu, S., Wang, Z., Yang, N. and Xu, J. (2019). Pedestrian dead reckoning using pocket-worn smartphone. IEEE Access, 7, 91063–91073. doi:10.1109/ACCESS.2019.2927053CrossRefGoogle Scholar