Investigation of bat echolocation calls using high resolution spectrogram and instantaneous frequency based analysis

This paper describes the study of bat echolocation signals using high resolution spectral analysis methods such as minimum variance estimator (MVE) and instantaneous frequency IF based analysis. The techniques reported in this paper is demonstrated to be capable of showing previously unseen features in the call structure of bat echolocation. It should be emphasised that although the study is focused on bat echolocation signals, the results are more generally applicable.

[1]  Jian Li,et al.  A new derivation of the APES filter , 1999, IEEE Signal Processing Letters.

[2]  Petros Maragos,et al.  Speech analysis and synthesis using an AM-FM modulation model , 1999, Speech Commun..

[3]  Lutz Wiegrebe,et al.  Time-variant spectral peak and notch detection in echolocation-call sequences in bats , 2008, Journal of Experimental Biology.

[4]  Marc W. Holderied,et al.  Echolocation calls produced by Kuhl's pipistrelles in different flight situations , 2007 .

[5]  Leon Cohen,et al.  Time Frequency Analysis: Theory and Applications , 1994 .

[6]  S. Parsons,et al.  Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks. , 2000, The Journal of experimental biology.

[7]  Boualem Boashash,et al.  Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals , 1992, Proc. IEEE.

[8]  I. Matsuo,et al.  An echolocation model for range discrimination of multiple closely spaced objects: transformation of spectrogram into the reflected intensity distribution. , 2004, The Journal of the Acoustical Society of America.

[9]  Petros Maragos,et al.  Speech formant frequency and bandwidth tracking using multiband energy demodulation , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[10]  James H. Fullard Echolocation assemblages and their effects on moth auditory systems , 1982 .

[11]  L. Mandel Interpretation of Instantaneous Frequencies , 1974 .

[12]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[13]  C. Findlay,et al.  EFFECTS OF CLUTTER ON ECHOLOCATION CALL STRUCTURE OF MYOTIS SEPTENTRIONALIS AND M. LUCIFUGUS , 2004 .

[14]  Steve McLaughlin,et al.  Investigation and Performance Enhancement of the Empirical Mode Decomposition Method Based on a Heuristic Search Optimization Approach , 2008, IEEE Transactions on Signal Processing.

[15]  J. Capon High-resolution frequency-wavenumber spectrum analysis , 1969 .

[16]  Patrick J. Loughlin,et al.  Time-varying frequencies of a signal , 1997, Optics & Photonics.