Unraveling Zero Crossing and Full Spectrum What does it all mean?

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Transcription:

Unraveling Zero Crossing and Full Spectrum What does it all mean? Ian Agranat Wildlife Acoustics, Inc. 2 nd Symposium on Bat Echolocation Research, Tucson AZ March 29, 2017

Let s start with a sound wave

Let s start with a sound wave

Zero crossing - observe the zero crossing points

Zero crossing Division Ratio (each Nth crossing)

Zero crossing Division Ratio (each Nth crossing) Measure crossing times in discrete microseconds Division ratio trades off frequency vs. time resolution

Full Spectrum Digitize the Analog Signal Measure discrete voltage levels at a discrete sample rate Resolve frequencies up to ½ sample rate (Nyquist) 16-bits = 96dB

Full Spectrum Analysis Fourier Transform NN 1 XX kk = xx nn ee iiiππππnn NN nn=0 Transforms N discrete timedomain samples into N/2 frequency bins with amplitude information

Full Spectrum Discrete Fourier Transform NN 1 XX kk = xx nn ee iiiππππnn NN nn=0 Transform size N trades off between frequency and time resolution (just like division ratio in ZC)

Now consider a noisy sound wave

Now consider a noisy sound wave In zero crossing, the signal is lost in the noise if the noise amplitude is larger than the signal s.

Now consider a noisy sound wave A threshold (instead of zero) can reduce sensitivity above the noise. But signals below the threshold won t be detected

Now consider a noisy sound wave In full spectrum, signal and noise are both represented faithfully within dynamic range

Now consider a noisy sound wave NN 1 XX kk = xx nn ee iiiππππnn NN nn=0 In full spectrum, noise power is divided and spread out among the frequency bins.

Signal to Noise Ratio (SNR) Signal to Noise Ratio determines How far can I detect a bat? White noise (e.g. self-noise of microphones) power is distributed across the frequency bandwidth. A native zero crossing detector has a large frequency bandwidth (e.g. 20-120kHz = ~100kHz bandwidth) Full spectrum analysis with Fourier transforms has a narrow frequency bandwidth (~1kHz bins) 10 log 10 ( 1,000 ) = 20dB full spectrum advantage over zero crossing 100,000 About 2.3 to 2.6X further detection distance (20-100kHz, 20⁰C, 50% R.H., FG sensor)

Native Zero Crossing vs. Zero Crossing Analysis Not the same thing! Recording in Zero Crossing has ~20dB disadvantage compared to recording in Full Spectrum (but has much lower power consumption and storage requirements making it attractive for some applications) Zero Crossing analysis from Full Spectrum recordings can have the same Full Spectrum advantage (Can also filter out insects, etc.)

Example: Native Zero Crossing vs. Full Spectrum What is going on here?

Example: Native Zero Crossing vs. Full Spectrum Native zero crossing interference from echoes, harmonics, other bats, background noise

Example: Native Zero Crossing vs. Full Spectrum Original full spectrum recording

Example: Native Zero Crossing vs. Full Spectrum Background noise reduced using sophisticated Digital Signal Processing techniques

Example: Native Zero Crossing vs. Full Spectrum More DSP techniques eliminate harmonics and echoes What is left (just the bat, no noise)

Example: Native Zero Crossing vs. Full Spectrum Zero crossing of enhanced full spectrum signal has full spectrum advantage Kaleidoscope does this!

Example: Native Zero Crossing vs. Full Spectrum Zero crossing of enhanced full spectrum signal has full spectrum advantage Kaleidoscope does this!

ZC vs. FS for species identification We notice an apparent correlation between call shape and power distribution. (Thanks Cori Lausen and Chris Corben!)

ZC vs. FS for species identification Let s try to calculate correlations on full spectrum recordings For full spectrum, we divide the frequency bandwidth into ~2kHz bins, calculate power spectra in each bin in db normalized to 0dB at the peak. We convert to zero crossing and calculate the log of dot times spent in each frequency bin, normalized to 0dB at the peak We calculate the R 2 correlation between the two curves by bin number and db value

Correlation of ZC call shape vs. FS power spectrum Across many species, most of the pulses have power spectra predicted by call shape. Many pulses are not correlated. Why?

Conclusions Recording in full spectrum is superior (by ~20dB) to recording in zero crossing, all else being equal Zero crossing analysis of full spectrum signals can enjoy the same 20dB advantage as full spectrum analysis Zero crossing does not have amplitude information from the original signal Maybe some amplitude information is helpful to identify some bat species But microphone frequency response and atmospheric absorption may have a larger effect on amplitude information. And call shape may predict amplitude information More study needed!

Thank you! Questions? This presentation can be found at: http://www.wildlifeacoustics.com/downloads/zcfs.pdf ian@wildlifeacoustics.com