Advertisement

Detection of Signals with Unknown Parameters

  • Bernard C. Levy
Chapter

Keywords

Doppler Frequency Detection Problem Fisher Information Matrix Radar Signal Doppler Frequency Shift 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    S. Haykin, Communication Systems, Fouth Edition. New York: J. Wiley & Sons, 2001.Google Scholar
  2. 2.
    I. F. Blake and W. C. Lindsey, “Level-crossing problems for random processes,” IEEE Trans. Informat. Theory, vol. 19, pp. 295–315, May 1973.CrossRefMATHMathSciNetGoogle Scholar
  3. 3.
    H. Cramér and M. R. Leadbetter, Stationary and Related Stochastic Processes– Sample Function Properties and Their Applications. New York: J. Wiley & Sons, 1967. Reprinted by Dover Publ., Mineola, NY, 2004.MATHGoogle Scholar
  4. 4.
    A. Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Processes, Fourth Edition. New York: McGraw Hill, 2002.Google Scholar
  5. 5.
    A. J. Laub, Matrix Analysis for Scientists and Engineers. Philadelphia, PA: Soc. for Industrial and Applied Math., 2005.CrossRefMATHGoogle Scholar
  6. 6.
    N. Levanon and E. Mozeson, Radar Signals. New York: J. Wiley/IEEE Press, 2004.CrossRefGoogle Scholar
  7. 7.
    D. Middleton and D. Van Meter, “Detection and extraction of signals in noise from the point of view of statistical decision theory. I,” J. Soc. Indust. Applied Math., vol. 3, pp. 192–253, Dec. 1955.CrossRefGoogle Scholar
  8. 8.
    D. Middleton and D. Van Meter, “Detection and extraction of signals in noise from the point of view of statistical decision theory. II,” J. Soc. Indust. Applied Math., vol. 4, pp. 86–119, June 1956.CrossRefGoogle Scholar
  9. 9.
    D. Middleton, An Introduction to Satistical Communication Theory. New York: McGraw-Hill, 1960. Reprinted by IEEE Press, New York, 1996.Google Scholar
  10. 10.
    E. J. Kelly, I. S. Reed, and W. L. Root, “The detection of radar echoes in noise. I,” J. Soc. for Indust. Applied Math., vol. 8, pp. 309–341, June 1960.CrossRefMathSciNetGoogle Scholar
  11. 11.
    E. J. Kelly, I. S. Reed, and W. L. Root, “The detection of radar echoes in noise. II,” J. Soc. for Indust. Applied Math., vol. 8, pp. 481–507, Sept. 1960.CrossRefMathSciNetGoogle Scholar
  12. 12.
    E. J. Kelly, “The radar measurement of range, velocity and acceleration,” IRE Trans. on Military Electron., vol. 5, pp. 51–57, 1961.CrossRefGoogle Scholar
  13. 13.
    H. L. Van Trees, Detection, Estimation and Modulation Theory, Part I: Detection, Estimation and Linear Modulation Theory. New York: J. Wiley & Sons, 1968. Paperback reprint edition in 2001.Google Scholar
  14. 14.
    S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory. Prentice-Hall, 1998.Google Scholar
  15. 15.
    C. W. Helstrom, Elements of Signal Detection & Estimation. Upper Saddle River, NJ: Prentice-Hall, 1995.MATHGoogle Scholar
  16. 16.
    R. N. McDonough and A. D. Whalen, Detection of Signals in Noise, Second Edition. San Diego, CA: Academic Press, 1995.Google Scholar
  17. 17.
    P. M. Woodward, Probability and Information Theory, with Applications to Radar. New York: Pergamon Press, 1953.MATHGoogle Scholar
  18. 18.
    W. Siebert, “A radar detection philosophy,” IEEE Trans. Informat. Theory, vol. 2, pp. 204–221, Sept. 1956.CrossRefGoogle Scholar
  19. 19.
    R. Price and E. M. Hofstetter, “Bounds on the volume and heights distributions of the ambiguity function,” IEEE Trans. Informat. Theory, vol. 11, pp. 207–214, Apr. 1965.CrossRefMathSciNetGoogle Scholar
  20. 20.
    H. L. Van Trees, Detection, Estimation and Modulation Theory, Part III: Radar-Sonar Signal Processing and Gaussian Signals in Noise. New York: J. Wiley & Sons, 1971. Paperback reprint edition in 2001.Google Scholar
  21. 21.
    A. Rihaczek, Principles of High-Resolution Radar. New York: McGraw-Hill, 1969.Google Scholar
  22. 22.
    P. Z. Peebles, Jr., Radar Principles. New York: J. Wiley & Sons, 1998.Google Scholar
  23. 23.
    A. L. Swindlehurst and P. Stoica, “Maximum likelihood methods in radar array signal processing,” Proeedings of the IEEE, vol. 86, pp. 421–441, Feb. 1998.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Bernard C. Levy
    • 1
  1. 1.University of CaliforniaDavisUSA

Personalised recommendations