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Design of Tightly Coupled INS/DVL/RPM Integrated Navigation System

강결합 방식의 INS/DVL/RPM 복합항법시스템 설계

  • Received : 2019.09.17
  • Accepted : 2019.10.21
  • Published : 2019.10.31

Abstract

Because the global positioning system (GPS) is not available in underwater environments, an inertial navigation system (INS)/doppler velocity log (DVL) integrated navigation system is generally implemented. In general, an INS/DVL integrated system adopts a loosely coupled method. However, in this loosely coupled method, although the measurement equation for the filter design is simple, the velocity of the body frame cannot be accurately measured if even one of the DVL transducer signals is not received. In contrast, even if only one or two velocities are measured by the DVL transducers, the tightly coupled method can utilize them as measurements and suppress the error increase of the INS. In this paper, a filter was designed to regenerate the measurements of failed transducers by taking advantage of the tightly coupled method. The regenerated measurements were the normal DVL transducer measurements and the estimated velocity in RPM. In order to effectively estimate the velocity in RPM, a filter was designed considering the effects of the tide. The proposed filter does not switch all of the measurements to RPM if the DVL transducer fails, but only switches information from the failed transducer. In this case, the filter has the advantage of being able to be used as a measurement while continuously estimating the RPM error state. A Monte Carlo simulation was used to determine the performance of the proposed filters, and the scope of the analysis was shown by the standard deviation ($1{\sigma}$, 68%). Finally, the performance of the proposed filter was verified by comparison with the conventional tightly coupled method.

Keywords

References

  1. Eliav, R., Klein, I., 2018 INS/Partial DVL Measurements Fusion with Correlated Process and Measurement Noise. Proceedings of the 5th International Electronic Conference on Sensors and Applications.
  2. Lee, P.M., Jeon, B.H., Kim, S.M., Lee, J.M., Lim, Y.K., Yang, S.I., 2004. A Hybrid Navigation System for Underwater Unmanned Vehicles, Using a Range Sonar. Journal of Ocean Engineering and Technology, 18(4), 33-39.
  3. Lee, J.M., Lee, P.M., Kim, S.M., Hong, S.W., SEO, J.W., Seong, W.J., 2003b. Rotating Arm Test for Assessment of an Underwater Hybrid Navigation System for a Semi-Autonomous Underwater Vehicle. Journal of Ocean Engineering and Technology, 17(4), 73-80.
  4. Lee, J.M., Lee, P.M., Seong, W.J., 2003a. Underwater Hybrid Navigation Algorithm Based on an Inertial Sensor and a Doppler Velocity Log Using an Indirect Feedback Kalman Filter. Journal of Ocean Engineering and Technology, 17(6), 83-90.
  5. Liu, P., Wang, B., Deng, Z., Fu, M., 2018. INS/DVL/PS Tightly Coupled Underwater Navigation Method With Limited DVL Measurements. IEEE Sensors Journal, 18(7), 2994-3002. https://doi.org/10.1109/JSEN.2018.2800165
  6. Rudolph, D.., Wilson, T., 2012. Doppler Velocity Log Theory and Preliminary Considerations for Design and Construction. Proceedings of the IEEE Southeastcon, Orlando FL, USA, 15-18. https://doi.org/10.1109/SECon.2012.6196918
  7. Titterton, D.H., Weston, J.L., 1997. Strapdown Inertial Navigation Technology. Peter Pegerinus Ltd., London.
  8. Yoo, T.S., Chung, G.P., Yoon, S.I., 2013. Development of Integrated Navigation Algorithm for Underwater Vehicle using Velocity Filter. Journal of Ocean Engineering and Technology, 27(2), 93-99. https://doi.org/10.5574/KSOE.2013.27.2.093
  9. Yoo, T.S., Kim, M.H. 2014. Analysis of Integrated Navigation Performance for Sensor Selection of Unmanned Underwater Vehicle (UUV). Journal of Ocean Engineering and Technology, 28(6), 566-573. https://doi.org/10.5574/KSOE.2014.28.6.566
  10. Tal, A., Klein, I., Katz, R., 2017. Inertial Navigation System/Doppler Velocity Log (INS/DVL) Fusion with Partial DVL Measurements. Sensors, 17(2), 415. https://doi.org/10.3390/s17020415