Abstract

This paper reports the development and preliminary experimental evaluation of a model-aided inertial navigation system (INS) for underwater vehicles. The implemented navigation system exploits accurate knowledge of the vehicle dynamics through an experimentally validated mathematical model, relating the water-relative velocity of the vehicle to the forces and moments acting upon it. Together with online current estimation, the model output is integrated in the navigation system. The proposed approach is of practical interest both for underwater navigation when lacking disparate velocity measurements, typically from a Doppler velocity log (DVL), and for systems where the need for redundancy and integrity is important, e.g. during sensor dropouts or failures, or in case of emergency navigation. The presented results verify the concept that with merely an addition of software and no added instrumentation, it is possible to considerably improve the accuracy and robustness of an INS by utilizing the output from a kinetic vehicle model. To the best of our knowledge, this paper is the first report on the implementation and experimental evaluation of model-aided INS for underwater vehicle navigation.

Highlights

  • Introduction refer toKinsey et al (2006) and references therein.In practice, a submersible does not have continuous Deciding which sensor outfit to include in an underwater position updates, a navigation solution based navigation system is important both from a performance solely on inertial navigation system (INS), and in particular low-cost INS, will have and cost perspective

  • A modelare used for resetting the INS and for obtaining the aided INS utilizing both external velocity measurements best possible estimate of the true vehicle state

  • Marine Control Systems: Guidance, Nav-This paper reports the development of a model-aided INS for underwater vehicle navigation

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Summary

Traditional INS

For (7) one must decide upon using either ν or νr The key components of any INS consist of an inertial as the velocity state. As discussed in Hegrenæs et al measurement unit (IMU) and a set of equations imple-. The navigation equations take the As is experimentally validated, the output gyro and accelerometer measurements from the IMU from an INS with neither position nor velocity measureas inputs and integrate them to velocity, position and ments in place, rapidly becomes useless. A modelare used for resetting the INS and for obtaining the aided INS utilizing both external velocity measurements best possible estimate of the true vehicle state A more detailed outline of the navigation systems is shown in Figure 3, differing only in the velocity aiding

Model-Aided INS
Data Post-Processing
Conclusions and Further Work
Further Work
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