# How can I improve the resolution of a spectrogram of a low-frequency signal with high sampling frequency (Python)?

Imagine you have signals $$x_1(t)$$ and $$x_2(t)$$ that contain a limited number of periods of low frequency oscillations and are sampled at 44100Hz (coming from an external source) and you want to obtain their spectrograms.

I chose nperseg=8820 to capture one period of 5Hz (44100/5=8820) in an analysis window and noverlap=1 to move in steps of one sample.

• As shown in the figure below, after zooming the frequency axis, the frequency resolution in this low-frequency region is poor. Are there ways to improve this resolution? By setting special parameters of the spectrogram function or by downsampling for instance?

• And why does the spectrogram of $$x_2(t)$$ change color over time?

import numpy

import scipy.signal
import matplotlib.pyplot as pplot

fs = 44100
t = numpy.linspace(0, 100000, 100001) / fs
x1 = numpy.sin(2*numpy.pi*5*t)
x2 = numpy.sin(2*numpy.pi*5*t**2)

f1, t1, Sxx1 = scipy.signal.spectrogram(x1, fs, nperseg=8820, noverlap=1)
f2, t2, Sxx2 = scipy.signal.spectrogram(x2, fs, nperseg=8820, noverlap=1)

pplot.figure(1)
pplot.clf()
pplot.subplot(2,2,1)
pplot.plot(t, x1)
pplot.subplot(2,2,2)
pplot.plot(t, x2)
pplot.subplot(2,2,3)
pplot.pcolormesh(t1, f1, Sxx1)
pplot.ylim([0, 30])
pplot.subplot(2,2,4)
pplot.pcolormesh(t2, f2, Sxx2)
pplot.ylim([0, 30])
pplot.show() • Probably yhere is a parameter defining the zero pedding. You can increase it. In some applications it is called nfft... Mar 14, 2020 at 20:42