An Efficient Integrated Attitude Determination Method Using Partially Available Doppler Measurement Under Weak GPS Environment
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In this paper, we propose a new and efficient method to achieve a three dimensional attitude determination through combining the Doppler measurement with INS (Inertial Navigation System) in a partial GPS (Global Positioning System) coverage environment. First, equations associating raw measurement with user velocity vector and overall filter framework are introduced. Then, this paper presents formulation deriving a reference velocity incremental vector based on the Doppler measurement, which consequentially serve as the measurement of the attitude determination filter. In generating the reference velocity incremental vector, all three cases are taken into account according to the availability conditions of satellite. First, for three or more visible satellites case, a least square method is used to fix the user velocity vector; for other partial satellite cases, a reference velocity incremental vector is generated by devising the best geometric prediction from the respective satellite measurements. In order to verify the performance of this study, flight experiment is carried out with sensor equipment onboard a manned aircraft. For demonstrating the efficiency of the presented algorithm, we examined the proposed algorithm using the onboard flight experimental data. As a result of comparative study with a conventional tightly coupled integration method, the proposed method demonstrated competent performance in both accuracy and computational efficiency under partial satellite visibility.
KeywordsAttitude determination Doppler efficiency flight experiment INS partial coverage velocity incremental vector
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- G. Blewitt, “Basics of the GPS technique: observation equations,” chapter in book Geodetic Applications of GPS, Swedish Land Survey, pp. 10–54, 1997.Google Scholar
- G. T. Schmidt and R. E. Phillips, INS/GPS Integration Architectures, Massachusetts Inst of Tech, Lexington, MA, pp. 1–18, 2010.Google Scholar
- M. George and S. Sukkarieh, “Tightly coupled INS/GPS with bias estimation for UAV applications,” Proc. of Australiasian Conference on Robotics and Automation (ACRA), 2005.Google Scholar
- C. Hide and T. Moore, “GPS and low cost INS integration for positioning in the urban environment,” Proc. of ION GPS, pp. 13–16, 2005.Google Scholar
- J. Wendel, O. Meister and R. Monikes, “Time-differenced carrier phase measurements for tightly coupled GPS/INS integration,” Proc. of IEEE/ION PLANS 2006, pp. 54–60, 2006.Google Scholar
- B. M. Scherzinger, “Precise robust positioning with inertial/GPS RTK,” Proc. of the 13th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GPS), pp. 115–162, 2000.Google Scholar
- Y. Li, J. Wang, C. Rizos, and P. Mumford, “Low-cost tightly coupled GPS/INS integration based on a nonlinear Kalman filtering design,” Proc. of ION National Technical Meeting, pp. 18–20, 2006.Google Scholar
- Navstar GPS Space Segment / Navigation User Interfaces (ICD-GPS-200C), IRN-200C-004, U.S. Air Force, Apr. 12, 2000. [Online]:http://www.navcen.uscg.gov/pubs/gps/ icd200/icd200cw1234.pdfGoogle Scholar
- M. Petovello, “How does a GNSS receiver estimate velocity?,” Inside GNSS, pp. 38–41, March/April 2015.Google Scholar
- B. Hofmann-Wellenhof, H. Lichtenegger, and E. Wasle, GNSS-global Navigation Satellite Systems: GPS, GLONASS, Galileo, and more, Springer Science & Business Media, 2007.Google Scholar