Open Access

Kalman Filter Realization for Orientation and Position Estimation on Dedicated Processor


Cite

1. Ahn H.-S., Won C.-H. (2009), DGPS/IMU Integration-Based Geolo-cation System: Airborne Experimental Test Results, Aerospace Science and Technology, 13, 316-324.10.1016/j.ast.2009.06.003Search in Google Scholar

2. Ali J., Ullah Baig Mirza M. R. (2010), Performance Comparison among Some Nonlinear Filters for a Low Cost SINS/GPS Integrated Solution, Nonlinear Dynamics, 61, 491-502.10.1007/s11071-010-9665-ySearch in Google Scholar

3. Bar-Shalom Y., Rong Li X., Kirubarajan T. (2001), Estimation with Applications to Tracking and Navigation, John Wiley & Sons.10.1002/0471221279Search in Google Scholar

4. Brookner E. (1998), Tracking and Kalman Filtering Made Easy, John Wiley & Sons.10.1002/0471224197Search in Google Scholar

5. Caron F., Duflos E., Pomorski D., Vanheegho P. (2006), GPS/IMU Data Fusion using Multisensor Kalman Filtering: Introduction of Contextual Aspects, Information Fusion, 7, 221-230.10.1016/j.inffus.2004.07.002Search in Google Scholar

6. Chen T., Xu S. (2010), Double Line-of-sight Measuring Relative Navigation for Spacecraft Autonomous Rendezvous, Acta Astro-nautica, 67, 122-134.10.1016/j.actaastro.2009.12.010Search in Google Scholar

7. Franca Junior J. A., Morgado J. A. (2010), Real Time Implementation of a Low-Cost INS/GPS System using xPC Target, Journal of Aerospace Engineering, Sciences and Applications, Vol. 2, No. 310.7446/jaesa.0203.04Search in Google Scholar

8. Gibbs B. P. (2011), Advanced Kalman Filtering, Least-Squares and Modelling, John Wiley & Sons.10.1002/9780470890042Search in Google Scholar

9. Gosiewski Z., Ortyl A. (1999), Algorithms of Inertial Guidance System and the Position of the Object of Spatial Motion (in Polish), Scientific Publishers Division of the Institute of Aviation system.Search in Google Scholar

10. Grewal M. S., Andrews A. P. (2008), Kalman Filtering: Theory and Practice Using MATLAB, John Wiley & Sons.10.1002/9780470377819Search in Google Scholar

11. Haid M., Breitenbach J. (2004), Low Cost Inertial Orientation Tracking with Kalman Filter, Applied Mathematics and Computation, 153, 567-575.10.1016/S0096-3003(03)00656-8Search in Google Scholar

12. Han S., Wang J. (2012), Integrated GPS/INS Navigation System with Dual-Rate Kalman Filter, GPS Solutions, 16, 389-404.10.1007/s10291-011-0240-xSearch in Google Scholar

13. Hongwei B., Zhihua J., Tian Wei F. (2006), IAE-adaptive Kalman Filter for INS/GPS Integrated Navigation System, Journal of Systems Engineering and Electronics, Vol. 17, No. 3, 502-508.Search in Google Scholar

14. Lee C. R., Salcic Z. (1997), High-performance FPGA-Based Implementation of Kalman Filter, Microprocessors and Microsystems, 21, 257-265.10.1016/S0141-9331(97)00040-9Search in Google Scholar

15. Luo Y., Wu W., He X. (2012), Double-filter Model with Modified Kalman Filter for Baseband Signal Pre-processing with Application to Ultra Tight GPS/INS Integration, GPS Solutions, 16, 463-476.10.1007/s10291-011-0246-4Search in Google Scholar

16. Mohamed A. H., Schwarz K. P. (1999), Adaptive Kalman Filtering for INS/GPS, Journal of Geodesy, 73, 193-203.10.1007/s001900050236Search in Google Scholar

17. Ning X., Fang J. (2007), An Autonomous Celestial Navigation Method for LEO Satellite Based on Unscented Kalman filter and Information Fusion, Aerospace Science and Technology, 11, 222-228.10.1016/j.ast.2006.12.003Search in Google Scholar

18. Pace S. (1996), The Global Positioning System: Policy Issues for an Information Technology, Space Policy, 12, 265-275.10.1016/0265-9646(96)00028-8Search in Google Scholar

19. Romaniuk S. (2013), Autopilot Measurement Systems Research, Master Thesis, Bialystok University of Technology.Search in Google Scholar

20. Rush J. (2000), Current Issues in the Use of the Global Positioning System Aboard Satellites, Acta Astronautica, 47, 377-387.10.1016/S0094-5765(00)00079-5Search in Google Scholar

21. Shojaei K., Mohammad Shahri A. (2011), Experimental Study of Iterated Kalman Filters for Simultaneous Localization and Mapping of Autonomous Mobile Robots, Journal of Intelligent and Robotic Systems, 63, 575-594.10.1007/s10846-010-9495-7Search in Google Scholar

22. Simon D. (2001), Kalman Filtering, Embedded Systems Programming, June 2001, 72-79.Search in Google Scholar

23.Sun W., Wang D., Xu L., Xu L. (2013), MEMS-Based Rotary Strapdown Inertial Navigation System, Measurement, 46, 2585-259610.1016/j.measurement.2013.04.035Search in Google Scholar

24. Titterton D. H., Weston J. L. (1997), Strapdown Inertial Navigation Technology, Institution of Electrical Engineers.Search in Google Scholar

25. Wagner J. F., Kasties G. (2004), Applying the Principle of Integrated Navigation Systems to Estimating the Motion of Large Vehicles, Aerospace Science and Technology, 8, 155-166.10.1016/j.ast.2003.09.006Search in Google Scholar

26. Wendel J., Schlaile C., Trommer G. F. (2001), Direct Kalman Filtering of GPS/INS for Aerospace Applications, International Symposium on Kinematic Systems in Geodesy, Geomatics and Navigation (KIS2001), Canada.Search in Google Scholar

27. http://www.aliexpress.com/Search in Google Scholar

28. http://www.armscontrol.org/documents/mtcrSearch in Google Scholar

29. http://www.gpsinformation.org/dale/nmea.htmSearch in Google Scholar

30. http://www.kamami.pl/Search in Google Scholar

31. https://www.sparkfun.com/Search in Google Scholar