Applications of Kalman Filtering in Aerospace 1960 to the Present

IEEE Control Systems

Volumn 30, Issue 3, 2010, Pages 69-78

  Grewal, Mohinder S ^a   Andrews, Angus P ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

AEROSPACE RESEARCH; KALMAN FILTER TECHNIQUE; KALMAN-FILTERING; LINEAR DIFFERENTIAL EQUATION; MANNED SPACECRAFT; NATIONAL ACADEMY OF ENGINEERING; NAVIGATION PROBLEM; OPTIMAL ESTIMATION METHODS; SOVIET UNION; STATE-SPACE; TIME DOMAIN;

COMPUTER SIMULATION; DIFFERENTIAL EQUATIONS; DIGITAL COMPUTERS; MANNED SPACE FLIGHT; NAVIGATION;

KALMAN FILTERS;

EID: 77952723426     PISSN: 1066033X     EISSN: None     Source Type: Journal    
DOI: 10.1109/MCS.2010.936465     Document Type: Article

References (31)

1. R. W. Bass. (2002). Some reminiscences of control and system theory in the period 1955–1960: Introduction of Dr. Rudolf E. Kalman. Real Time. (Spring/Summer Issue), pp. 2–6. [Online]. Available: www.ece.uah.edu/PDFs/news/RT-sprsum2002.pdf
2. R. S. Bucy and J. T. Lo, “Seminal contributions of Bob Bass to control,” in Proc. 1998 American Control Conf., 1998, pp. 411–414.
3. W. Berry and C. Loeb, “Breakthrough Air Force capabilities spawned by basic research,” Center for Technol. and Natl. Security Policy, Natl. Defense Univ., Washington, D.C., Defense & Technology Paper No. 39, Apr. 2007.
4. M. S. Grewal and A. P. Andrews, Kalman Filtering: Theory and Practice Using MATLAB, 3rd ed. Hoboken, NJ: Wiley, 2008.
5. R. E. Kalman, “A new approach to linear filtering and prediction problems,” ASME Trans., J. Basic Eng., ser. D., vol. 82, pp. 35–45, 1960.
6. R. E. Kalman and R. S. Bucy, “New results in linear prediction and filtering theory,” ASME Trans., J. Basic Eng., ser. D., vol. 83, pp. 95–108, 1961.
7. P. Swerling, “First order error propagation in a stagewise differential smoothing procedure for satellite observations,” J. Astronaut. Sci., vol. 6, pp. 46–52, 1959.
8. S. F. Schmidt, “The Kalman filter: Its recognition and development for aerospace applications,” AIAA J. Guid. Contr., vol. 4, pp. 4–7, 1981.
9. R. H. Battin, “Space guidance evolution—A personal narrative,” AIAA J. Guid. Contr., vol. 5, pp. 97–110, 1982.
10. E. C. Hall, J ourney to the Moon: The History of the Apollo Guidance Computer. Washington, D.C.: American Institute of Aeronautics and Astronautics, 1996.
11. A. S. Morris and M. J. H. Sterling, “Model tuning using the extended Kalman filter,” Electron. Lett., vol. 15, pp. 201–202, Mar. 1979.
12. D. MacKenzie, Inventing Accuracy: A Historical Sociology of Nuclear Missile Guidance. Cambridge, MA: MIT Press, 1993.
13. M. Schuler, “Die Storung von Pendul und Kreiselapparaten durch die Beschleunigung der Fahrzeuges,” Physikalische Zeitschrift, vol. 24, pp. 344–350, 1923.
14. M. S. Grewal, V. Henderson, and R. Miyasako, “Application of Kalman filtering to the calibration and alignment of inertial navigation systems,” IEEE Trans. Automat. Contr., vol. 36, no. 1, pp. 4–14, Jan. 1991.
15. M. S. Grewal, L. R. Weill, and A. P. Andrews, Global Positioning Systems, Inertial Navigation, and Integration, 2nd ed. Hoboken, NJ: Wiley, 2007.
16. W. R. Fried, “Principles and simulation of JTIDS relative navigation,” IEEE Trans. Aerosp. Electron. Syst., vol. AES-14, pp. 76–84, Jan. 1978.
17. J. E. Anderson, “Magnetic anomaly detection frequency responses,” Naval Air Development Center, Warminster, Pennsylvania, Rep. ADCEC-47-51, Oct. 1949.
18. A. P. Andrews, “The accuracy of navigation using magnetic dipole beacons,” Navigation, vol. 38, pp. 367–397, Winter 1991–1992.
19. F. C. Schweppe, “Evaluation of likelihood functions for Gaussian signals,” IEEE Trans. Inform. Theory, vol. IT-11, pp. 61–70, 1965.
20. R. E. Parsons and W.-B. Zhang. (1988 Oct.). Lateral guidance systems requirements definition, program on advanced technology for the highway, Univ. of California at Berkeley, Research Rep. UCB-ITSPRR-88-l [Online]. Available: www.path.berkeley.edu/path/publications/pdf/PRR/88/PRR-88-01.pdf
21. R. K. Mehra, “On the identification of variance and adaptive Kalman filtering,” IEEE Trans. Automat. Contr., vol. 15, pp. 175–184, 1970.
22. R. K. Mehra, “Approaches to adaptive filtering,” IEEE Trans. Automat. Contr., vol. 17, pp. 693–698, 1972.
23. M. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Processing, vol. 50, pp. 174–188, Feb. 2002.
24. R. van der Merwe and E. Wan, “Gaussian mixture sigma-point particle filters for sequential probabilistic inference in dynamic state-space models,” in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP), Hong Kong, 2003, pp. 701–704.
25. S. J. Julier and J. K. Uhlmann, “Unscented filtering and nonlinear estimation,” Proc. IEEE, vol. 92, pp. 401–422, 2004.
26. P. Houtekamer and H. L. Mitchell, “Data assimilation using an ensemble Kalman filter technique,” Monthly Weather Rev., vol. 126, pp. 796–811, 1998.
27. J. L. Anderson and S. L. Anderson, “A Monte Carlo implementation of the nonlinear filtering problem to produce assimilations and forecasts,” Monthly Weather Rev., vol. 127, pp. 2741–2759, 1999.
28. Y. Gao, E. J. Krakiwsky, M. A. Abousalem, and J. F. McLellan, “Comparison and analysis of centralized, decentralized, and federated filters,” Navigation, vol. 40, pp. 69–86, Spring 1993.
29. P. D. Joseph and J. T. Tou, “On linear control theory,” AIEE Trans. Applicat. Ind., vol. 80, pp. 193–196, 1961.
30. M. Athans, “The role and use of the stochastic linear-quadratic-Gaussian problem in control system design,” IEEE Trans. Automat. Contr., vol. AC-16, pp. 529–552, 1971.
31. R. S. Bucy and P. D. Joseph, Filtering for Stochastic Processes with Applications to Guidance, 2nd ed. New York, NY: Chelsea Publishing, 1987.