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Real-Time Implementation of GPS Aided Low-Cost Strapdown Inertial Navigation System

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Abstract

This work details the study, development, and experimental implementation of GPS aided strapdown inertial navigation system (INS) using commercial off-the-shelf low-cost inertial measurement unit (IMU). The data provided by the inertial navigation mechanization is fused with GPS measurements using loosely-coupled linear Kalman filter implemented with the aid of MPC555 microcontroller. The accuracy of the estimation when utilizing a low-cost inertial navigation system (INS) is limited by the accuracy of the sensors used and the mathematical modeling of INS and the aiding sensors’ errors. Therefore, the IMU data is fused with the GPS data to increase the accuracy of the integrated GPS/IMU system. The equations required for the local geographic frame mechanization are derived. The direction cosine matrix approach is selected to compute orientation angles and the unified mathematical framework is chosen for position/velocity algorithm computations. This selection resulted in significant reduction in mechanization errors. It is shown that the constructed GPS/IMU system is successfully implemented with an accurate and reliable performance.

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References

  1. Noureldin, A., Karamat, T.B., Eberts, M.D., El-Shafie, A.: Performance enhancement of MEMS-based INS/GPS integration for low-cost navigation applications. IEEE Trans. Veh. Technol. 58(3), 1077–1096 (2009)

    Article  Google Scholar 

  2. Schelling, R.: A low-cost angular rate sensor for automotive applications in surface micromachining technology. In: Third Annual International Conference on Advanced Microsystems for Automotive Applications Proceedings (1999)

  3. Wu, Z.C., Wang, Z.F., Ge, Y.: Gravity based online calibration of monolithic tri-axial accelerometers gain and offset drift. In: Proceedings of 4th World Congress on Intelligent Control and Automation (2002)

  4. Chatfield, A.B.: Fundamentals of High Accuracy Inertial Navigation. American Institute of Aeronautics and Astronautics, Reston (1997)

  5. Skog, I., Handel, P.: Calibration of MEMS inertial measurement unit. In: XVII IMEKO World Congress, Metrology for a Sustainable Development (2006)

  6. Sukkarieh, S.: Low Cost, High Integrity, Aided Inertial Navigation Systems for Autonomous Land Vehicles. Ph.D. dissertation, Mechanical and Mechatronic Engineering, Australian Centre for Field Robotics, The University of Sydney, Sydney, Australia (2000)

  7. Titterton, D., Weston, W.: Strapdown Inertial Navigation Technology, 2nd edn. The Institute of Electrical Engineers (IEE), Virginia (2004)

    Google Scholar 

  8. Savage, P.G.: A unified mathematical framework for strapdown algorithm design. J. Guid. Control Dyn. 29(2), 237–249 (2006)

    Article  Google Scholar 

  9. Kong, X.: Inertial Navigation System Algorithms for Low Cost IMU. Ph.D. dissertation, Aerospace, Mechanical and Mechatronic Engineering, Australian Centre for Field Robotics, The University of Sydney, Sydney, Australia (2000)

  10. Meskin, D.G., Bar-Ithack, I.Y.: Unified approach to inertial navigation system error modeling. J. Guid. Control Dyn. 15(3), 648–653 (1992)

    Article  MATH  Google Scholar 

  11. Hung, J.C., Thacher, J.R., White, H.V.: Calibration of accelerometer triad of an IMU with drifting Z—accelerometer bias. In: Proceeding NAECON 1989, IEEE Aerospace and Electronics Conference, vol. 1, pp. 153–158 (1989)

  12. Rogers, R.M.: Applied Mathematics in integrated Navigation Systems, 2nd edn. AIAA Education Series (2003)

  13. Baselgaal, S., Garcia-Asenjoa, L., Garriguesa, P., Lermaa, J.L.: Inertial navigation system data filtering prior to GPS/INS integration. J. Navig. 62(4), 711–720 (2009)

    Article  Google Scholar 

  14. Bar-Itzhack, I.Y.: Identity between INS position and velocity error models. J. Guid. Control, 4, 568–570 (1981)

    Article  Google Scholar 

  15. Analog Devices Inc.: ADXL202EB Dual Axis Accelerometer Evaluation Board Data Sheet (Rev. A). Online: http://www.analog.com

  16. Analog Devices Inc.: ADXRS150EB Single Chip Rate Gyro Evaluation Board. Online: http://www.analog.com

  17. Sahawneh, L.: Real-time implementation of gps aided low-cost strapdown inertial navigation system. Master’s thesis, College of Engineering, American University of Sharjah (2009)

  18. Excelmachinetools Inc.: Excel Dividing Heads Semi Universal and HV6 Excel Precision Rotary Tables, 1995–2008

  19. Maybeck, P.S.: Stochastic Models, Estimation, and Control, vols. 1 and 2. Academic (1982)

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Correspondence to Mamoun F. Abdel-Hafez.

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Sahawneh, L.R., Al-Jarrah, M.A., Assaleh, K. et al. Real-Time Implementation of GPS Aided Low-Cost Strapdown Inertial Navigation System. J Intell Robot Syst 61, 527–544 (2011). https://doi.org/10.1007/s10846-010-9501-0

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  • DOI: https://doi.org/10.1007/s10846-010-9501-0

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