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#Difference between loaded questions game variations windows

for the elevation angle (bottom panel) the methods are separated by 10 deg. In the top panel, which shows the azimuth the different methods are separated by 20 deg. Worst is the Roth method, COTS and PHAT are slightly worse than CC as seen in following picture

Widely spaced sensors will have different background noise and uncorrelated signals, but closely spaced sensors will very likely only differ by time delay (phase shifts).įor my underwater click direction finding, the CC method (no spectral weighting) performs best. This means, that while peak is sharp, the location of the peak is uncertain, consistent with the widening aspect talked about in the literature.įinal selection will has to consider signal and background noise characteristics. Literature states that Roth and SCOT methods broaden the correlation peak, but this is very much likely a statement for (wide-sense-stationary) noise signals, as I cannot see this for the cetacean clicks shown in above picture.Įdit: while the peak in picture seems sharper for all but CC, the variability of the peak location is worse for all but CC.

PHAT: effectively whitens the cross spectra (seems to be an ad-hoc method simplifying the Maximum Likelihood method).

SCOT: both channels have different power spectra.

Roth: both channels have same power spectra.

CC: noise spectrum is already flat, no further action required.

The x-axis are samples and the data are from underwater recordings of a cetacean click recorded on two closely spaced hydrophonesĮdit: The purpose of of methods (with exception of the CC method) is to pre-whiten the noise (flatten the spectrum), so one could conclude: With exception of the plain CC all weighted methods are sharper with more or less similar noise levels. The purpose of time-domain filters are to reduce the influence of off-band noise.Īs I was myself interested in the differences and I'm working exactly on the same problem (multi-channel delay estimation) I applied the four methods and got the following picture

The different methods you present are multiplications in the frequency domain and as such they are filters in time domain. Acoustic source localization based on generalized cross-correlation time-delay estimation. A table (from 1) with the window functions is pasted below:ĬC: cross-correlation, SCOT: Smoothed Coherence Transform, PHAT: Phase TransformĬould someone provide a broad explanation of when to use each of the types? Most of the papers I've found study the effect of one or the other types, or describe the types and compare them for their audio data, or list out the window functions for each type. I've empirically noticed there is some difference in how much each of these GCC types affects peak detection - and have also read each of the types is best for a particular type of audio situation (refs: Sig Proc SE).

#Difference between loaded questions game variations windows

Likelihood) - which are basically different windows applied before the inverse FFT is applied. I also understand that there are multiple types of GCC (PHAT, SCOT, Roth, Hanan-Thomson/Max. I'm trying to use the generalised cross-correlation (GCC) to find time-difference esimates acoss my multi-channel data.