Detection in a Non-Gaussian Environment: Weak and Fading Narrowband Signals

  • Stuart C. Schwartz
  • John B. Thomas

Abstract

Procedures for the detection of both weak and narrowband signals in non–Gaussian noise environments are discussed. For the weak signal case, nonlinear processors based on the Middleton Class A noise model and the mixture representation are developed. Significant processing gains are achievable with some rather simple procedures. A variant of the mixture model leads to a nonstationary detector, called the “switched detector.” Experiments with this detector on ambient arctic and shrimp noises show processing gains of 1.4 to 4.1 dB, respectively.

Signals with a moderate signal-to-noise ratio in non-Gaussian noise are modeled as fading narrowband signals. A new processor is developed which combines a robust estimator (for the fading signal) with a robust detection procedure. The robust estimator-detector prserves the structure of the quadrature (envelope) matched filter and is shown to be asymptotically optimal for a wide range of decision rules and several common target models encountered in sonar and radar. Various degrees of robustness are achieved, depending on the assumed availability for noise reference samples.

Keywords

Radar Expense Acoustics Sonar Univer 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Middleton, D., “Statistical–Physical Models of Electromagnetic Interference,” IEEE Trans. Electromgn. Compat, Vol. EMC–19, pp. 106–127, August 1977.Google Scholar
  2. 2.
    Middleton, D., “Canonical non–Gaussian Noise Models: Their Implications for Measurement and for Prediction of Receiver Performance,” IEEE Trans. Electromgn. Compat, Vol. EMC–21, pp. 209–220, August 1979.Google Scholar
  3. 3.
    Spaulding, A.D., Middleton, D., “Optimum Reception in an Impulsive Interference Environment–Part I: Coherent Detection,” IEEE Trans. Comm, Vol. COM– 25, No. 9, pp. 910–923, September 1977.MATHCrossRefGoogle Scholar
  4. 4.
    Berry, L.A., “Understanding Middleton’s Canonical Formula for Class A Noise,” IEEE Trans. Electromgn. Compat, Vol. EMC–23, No. 4, pp. 337–343, November 1981.Google Scholar
  5. 5.
    Vastola, K.S., “Threshold Detection in Narrow–Band Non–Gaussian Noise,” IEEE Trans. Comm, Vol. COM–32, No. 2, pp. 134–139, February 1984.CrossRefGoogle Scholar
  6. 6.
    Vastola, K.S., Schwartz, S.C., “Suboptimal Threshold Detection in Narrowband Non–Gaussian Noise,” Proc., IEEE Intl. Conf, on Comm, Boston, MA, pp. 1608– 1612, June 1983.Google Scholar
  7. 7.
    Schwartz, S.C., Vastola, K.S., “Detection of Stochastic Signals in Narrowband Non–Gaussian Noise,” Proc. IEEE Conf, on Decision and Control, San Antonio, TX, pp. 1106–1109, December 1983.Google Scholar
  8. 8.
    Czarnecki, S.V., Thomas, J.B., Nearly Optimal Detection of Signals in Non-Gaussian Noise, T.R. #14, Dept. of Electrical Engineering, Princeton University, Princeton, NJ, February 1984.Google Scholar
  9. 9.
    Czarnecki, S.V., Thomas, J.B., “Signal Detection in Bursts of Impulsive Noise,” Proc., 1988 Conference on Information Sciences and Systems, Johns Hopkins University, Baltimore, MD, pp. 212–217, March 1983.Google Scholar
  10. 10.
    Willett, P.K., Thomas, J.B., “The Analysis of Some Undersea Noise with Applications to Detection,” Proc., 24th Annual Allerton Conference on Communication, Control, and Computing, Urbana, IL, pp. 266–275, October 1986.Google Scholar
  11. 11.
    Helstrom, C.W., Statistical Theory of Signal Detection, Oxford, Pergamon Press, 1968.Google Scholar
  12. 12.
    Weiss, M., Schwartz, S.C., Robust Detection of Fading Narrow–Band Signals in Non–Gaussian Noise, T.R. #17, Dept. of Electrical Engineering, Princeton University, Princeton, NJ, February 1985.Google Scholar
  13. 13.
    Shin, J.G., Kassam, S.A., “Robust Detection for Narrowband Signals in non-Gaussian Noise,” J. Acoust. Soc. America, Vol. 74, pp. 527–533, August 1983.CrossRefGoogle Scholar
  14. 14.
    Weiss, M., Schwartz, S.C., “Robust Detection of Coherent Radar Signals in Nearly Gaussian Noise,” Proc., IEEE Intl. Radar Conference, Arlington, VA, pp. 297–302, May 6–9, 1985.Google Scholar
  15. 15.
    Weiss, M., Schwartz, S.C., “Robust Scale Invariant Detection of Coherent Narrowband Signals in Nearly Gaussian Noise,” Proc., IEEE Intl. Conf. on Acoustics, Speech, and Signal Processing, Tampa, FL, pp. 1281–1284, March 1985.Google Scholar
  16. 16.
    Weiss, M., Schwartz, S.C., Robust and Nonparametric Detection of Fading Narrowband Signals, T.R. #19, Dept. of Electrical Engineering, Princeton University, Princeton, NJ, January 1986.Google Scholar

Copyright information

© Springer-Verlag New York Inc. 1989

Authors and Affiliations

  • Stuart C. Schwartz
    • 1
  • John B. Thomas
    • 1
  1. 1.Department of Electrical EngineeringPrinceton UniversityPrincetonUSA

Personalised recommendations