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Animal Sonar pp 797-802 | Cite as

Time-Frequency Processing of Bat Sonar Signals

  • Patrick Flandrin
Part of the NATO ASI Science book series (NSSA, volume 156)

Abstract

It is known that time-frequency distributions can be used for the demodulation of bat sonar signals and, in some cases, for detection-estimation tasks via a 2-D correlation process. In this paper, we formalize the intuitive notion of correlation of time-frequency structures in the simplified case of AM + FM signals. This results in a general time-frequency receiver structure depending only on a time-frequency smoothing function. According to the choice of this smoothing, it is shown that the receiver can vary continuously from a semi-coherent (matched filter and envelope detector) to a non-coherent (energetic) one. This suggests that both can be viewed as limiting cases of a unique time-frequency processing. The proposed approach is illustrated on the detection of echoes (over water) of signals emitted by Myotis daubentoni and recorded in the field.

Keywords

Matched Filter Wigner Distribution Echolocation Call Envelope Detector Eptesicus Fuscus 
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.

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References

  1. [1]
    W. Martin, K. Kruger-Alef, Application of the Wigner-Ville spectrum to the spectral analysis of a class of bio-acoustical signals blurred by noise, in: Proc. CNRS Conf. Airborne Animal Sonar Systems, pp. 18.1–18.25, Lyon, 1985.Google Scholar
  2. [2]
    R. A. Altes,Echolocation as seen from the viewpoint of radar/sonar theory, in: Localization and Orientation in Biology and Engineering, Varju/Schnitzler, eds., pp. 234–244, Springer, 1984.Google Scholar
  3. [3]
    R. A. Altes,Detection, estimation and classification with spectrograms, J. Acoust. Soc. Am., 67 (4), pp. 1232–1246, 1980.CrossRefGoogle Scholar
  4. [4]
    T.A.C.M. Claasen, W.F.G. Mecklenbrauker, The Wigner distribution–A tool for time-frequency signal analysis, Philips J. Res., 35, pp. 217–250, 276–300, 372–389, 1980.Google Scholar
  5. [5]
    W. Martin, P. Flandrin, Wigner-Ville spectral analysis of non-stationary processes, IEEE Trans. on ASSP, ASSP-33 (6), pp. 1461–1470, 1985.CrossRefGoogle Scholar
  6. [6]
    S. Kay, G. F. Boudreaux-Bartels, On the optimality of the Wigner distribution for detection, in: Proc. IEEE ICASSP’85, pp. 1017–1029, Tampa, 1985.Google Scholar
  7. [7]
    P. Flandrin, On detection-estimation procedures in the time-frequency plane, in: Proc. IEEE ICASSP’86, pp. 2331–2334, Tokyo, 1986.Google Scholar
  8. [8]
    B. MØh1,Detection by a Pipistrelle bat of normal and reversed replica of its sonar pulses, in: Proc. CNRS Conf. Airborne Animal Sonar Systems, pp. 7.1–7.22, Lyon, 1985.Google Scholar
  9. [9]
    D. Menne, H. H.Ckbarth,Accuracy of distance measurement in the bat Eptesicus fuscus: Theoretical aspects and computer simulations, J. Acoust. Soc. Am., 79 (2), pp. 386–397, 1986.PubMedCrossRefGoogle Scholar

Copyright information

© Plenum Press, New York 1988

Authors and Affiliations

  • Patrick Flandrin
    • 1
  1. 1.Laboratoire de Traitement du SignalUA 346 CNRS ICPILyon Cedex 02France

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