glfer - Online in the Cloud

PROGRAM:

NAME

glfer - spectrogram display and QRSS keyer

SYNOPSIS

glfer [OPTIONS] ...

DESCRIPTION

glfer is a program that displays the power spectrum of a signal as a function of time in a
format known as a waterfall display; this is also called a spectrogram. The horizontal
axis represents time. The time scale depends on the sample rate and the number of points
per FFT. The vertical axis represents frequency, from DC to the Nyquist frequency (half
the sample rate). The estimated power of the input signal is indicated by the color; the
spectrogram window has an automatic gain control (AGC) that ensures always the maximum
visual contrast and which, in the current version, cannot be disabled.

Resizing the main window in the horizontal direction just changes the length of the time
scale; resizing it in the vertical direction enlarges the portion of spectrum shown in the
window. The entire spectrum can be seen by scrolling the spectrogram window using the
scrollbar on the right. Moving the mouse pointer on the spectrogram window shows the
frequency corresponding to the pointer position and the signal power at that frequency on
the status line at the bottom.

The first time glfer is run it will ask to select a control port (serial or parallel) for
the TX keying functions; if the mouse is connected to the serial port be sure NOT to
select its serial port for controlling the TX otherwise the system may hang. All the
settings can be saved to a configuration file; in this case they will be automatically
loaded when glfer is launched.

Please note that the program must be run as root (or suid root) to gain access to the
transmitter control (parallel or serial) port.

You may have to use a separate mixer program to adjust the input volume and to enable the
desired input.

SPECTRAL ESTIMATORS

glfer can use several different spectral estimators to compute the input signal power
spectrum:

Periodogram
the "classical" periodogram, which is obtained as the squared amplitude of the discrete
Fourier transform, after tapering the data with a "window function" selectable among the
Hanning, Blackman, Gaussian, Welch, Bartlett, Rectangular, Hamming and Kaiser types. As
usual, the FFT number of points and the overlap between data blocks can be freely changed.

Multitaper method
The multitaper method is a weighted combination of periodograms computed with different
windows, all belonging to the same family and having certain peculiar properties.

This method was described by David J. Thomson in "Spectrum Estimation and Harmonic
Analysis", Proc. IEEE, vol.70, Sep. 1982. Besides the FFT size and overlap, it is
possible to change also a relative bandwidth parameter and the number of windows to use
for the analysis.

This method requires more CPU power than the first one, due to the fact that several FFTs
are performed on the same block of data, using different windows. The resulting spectrum
is similar to a classical periodogram, but with much less variance (i.e. less variation in
the background noise [speckle]). Performances are also similar to the periodogram, maybe
it makes detection of QRSS signals a little easier, but this doesn't means they are always
more readable.

High performance ARMA
The (so called) "high performance" ARMA model assumes that the input signal is composed
only of white noise plus a certain number of sinusoids and tries to extract the relevant
parameters (sinusoids frequency and strenght) from the data.

Reference article for this implementation is "Spectral An Overdetermined Rational Model
Equation Approach", by James A. Cadzow, Proc. IEEE, vol.70, Sep. 1982.

At present this method is still experimental. There are two parameters that can be varied:
t is the number of samples used for computing the samples autocorrelation and p_e is the
order of the AR model. This latter must be less than t, and both number should be fairly
small in order not to overload the CPU. The number of sinusoids is estimated autimatically
from the samples autocorrelation. Use the default numbers as a starting point and
experiment! Unfortunately this spectral estimator performs poorly with non-white noise
(as we have usually in the RX audio, due to the IF filters) and high noise levels. On the
other hand it provides a very good visual SNR with signals not buried in the noise

LMP
This method is experimental

OPTIONS

-d, --device FILE
use FILE as audio device (default: /dev/dsp)

-f, --file FILENAME
take audio input from FILENAME (WAV format)

-s, --sample_rate RATE
set audio sample rate to RATE Hertz (default: 8000)

-n N number of points per FFT to N (preferably a power of 2, default: 1024)

-h, --help
print the help

-v, --version
display the version of glfer and exit

Use glfer online using onworks.net services