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Applied Optics

Applied Optics


  • Vol. 23, Iss. 12 — Jun. 15, 1984
  • pp: 1960–1966

Optical Kalman filtering for missile guidance

David Casasent, Charles P. Neuman, and John Lycas  »View Author Affiliations

Applied Optics, Vol. 23, Issue 12, pp. 1960-1966 (1984)

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Optical systolic array processors constitute a powerful and general-purpose set of optical architectures with high computational rates. In this paper, Kalman filtering, a novel application for these architectures, is investigated. All required operations are detailed; their realization by optical and special-purpose analog electronics are specified; and the processing time of the system is quantified. The specific Kalman filter application chosen is for an air-to-air missile guidance controller. The architecture realized in this paper meets the design goal of a fully adaptive Kalman filter which processes a measurement every 1 msec. The vital issue of flow and pipelining of data and operations in a systolic array processor is addressed. The approach is sufficiently general and can be realized on an optical or digital systolic array processor.

© 1984 Optical Society of America

Original Manuscript: January 20, 1984
Published: June 15, 1984

David Casasent, Charles P. Neuman, and John Lycas, "Optical Kalman filtering for missile guidance," Appl. Opt. 23, 1960-1966 (1984)

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  1. H. J. Caulfield et al., “Optical Implementation of Systolic Array Processing,” Opt. Commun. 40, 86 (1981. [CrossRef]
  2. D. Casasent, “Acoustooptic Transducers in Iterative Optical Vector–Matrix Processors,” Appl. Opt. 21, 1859 (1982). [CrossRef] [PubMed]
  3. D. Casasent, J. Jackson, C. Neuman, “Frequency-Multiplexed and Pipelined Iterative Optical Systolic Array Processors,” Appl. Opt. 22, 115 (1983). [CrossRef] [PubMed]
  4. R. P. Bocker, H. J. Caulfield, K. Bromley, “Rapid Unbiased Bipolar Incoherent Calculator Cube,” Appl. Opt. 22, 804 (1983). [CrossRef] [PubMed]
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  6. M. Carlotto, D. Casasent, “Microprocessor-Based Fiber-Optic Iterative Optical Processor,” Appl. Opt. 21, 147 (1982). [CrossRef] [PubMed]
  7. D. Casasent, C. P. Neuman, M. Carlotto, “An Electro-Optical Processor for Optimal Control,” Proc. Soc. Photo-Opt. Instrum. Eng. 295, 176 (1981).
  8. C. P. Neuman, D. Casasent, R. Baumbick, “An Electro-Optical Processor for the Optimal Control of F100 Aircraft Engines,” in Proceedings Electro-Optical Systems Design Conference (Industrial & Scientific Conference Management, Chicago, 1981), pp. 311–320.
  9. J. Jackson, D. Casasent, “State Estimation Kalman Filter Using Optical Processing: Noise Statistics Known,” Appl. Opt. 23, 376 (1984). [CrossRef] [PubMed]
  10. R. H. Travassos, “Real-Time Implementation of Systolic Kalman Filters,” Proc. Soc. Photo-Opt. Instrum. Eng. 431, 97 (1983).
  11. W. A. Roemer, P. S. Maybeck, “An Optically Implemented Multiple-Stage Kalman Filter Algorithm,” Proc. Soc. Photo-Opt. Instrum. Eng. 431, 221 (1983).
  12. R. L. Barron et al., “A New Class of Guidance Laws for Air-To-Air Missiles,” in Proceedings, Third Meeting of the Coordinating Group on Modern Control Theory, Part 1 (Oct.1081), pp. 20–21.
  13. T. L. Riggs, P. L. Vergez, “Advanced Air-To-Air Missile Guidance Using Optimal Control and Estimation,” Report on Contrast AFATL/DLMA, AFATL-TR-81-56 (June1981).
  14. P. S. Maybeck, Stochastic Models, Estimation, and Control, Vol. 1, (Academic, New York, 1979).
  15. A. Gelb, Applied Optimal Estimation (MIT Press, Cambridge, Mass., 1974).
  16. A. E. Bryson, Y. C. Ho, Applied Optical Control (Blaisdell, Waltham, Mass., 1969).
  17. R. S. Varga, Matrix Iterative Analysis (Prentice-Hall, Englewood Cliffs, N.J., 1962).
  18. R. E. Bellman, R. E. Kalaba, Quasilinearization and Nonlinear Boundary-Value Problems (Elsevier, New York, 1965).
  19. T. R. Blackburn, “Solution of the Algebraic Matrix Riccati Equation via Newton-Raphson Iteration,” AIAA J. 6, 951 (1968). [CrossRef]

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