Choosing the Correct Smoothing Window

Selecting a smoothing window is not a simple task. Each smoothing window has its own characteristics and suitability for different applications. To choose a smoothing window, you must estimate the frequency content of the signal. If the signal contains strong interfering frequency components distant from the frequency of interest, choose a smoothing window with a high side lobe roll-off rate. If the signal contains strong interfering signals near the frequency of interest, choose a smoothing window with a low maximum side lobe level.

If the frequency of interest contains two or more signals very near to each other, spectral resolution is important. In this case, it is best to choose a smoothing window with a very narrow main lobe. If the amplitude accuracy of a single frequency component is more important than the exact location of the component in a given frequency bin, choose a smoothing window with a wide main lobe. If the signal spectrum is rather flat or broadband in frequency content, use the uniform window, or no window. In general, the Hanning window is satisfactory in 95% of cases. It has good frequency resolution and reduced spectral leakage. If you do not know the nature of the signal but you want to apply a smoothing window, start with the Hanning window.

The table below lists different types of signals and the appropriate windows that you can use with them.

Type of Signal Window

Transients whose duration is shorter than the length of the window

Rectangular

Transients whose duration is longer than the length of the window

Exponential, Hanning

General-purpose applications

Hanning

Spectral analysis (frequency-response measurements)

Hanning (for random excitation), Rectangular (for pseudorandom excitation)

Separation of two tones with frequencies very close to each other but with widely differing amplitudes

Kaiser-Bessel

Separation of two tones with frequencies very close to each other but with almost equal amplitudes

Rectangular

Accurate single-tone amplitude measurements

Flat top

Sine wave or combination of sine waves

Hanning

Sine wave and amplitude accuracy is important

Flat top

Narrowband random signal (vibration data)

Hanning

Broadband random (white noise)

Uniform

Closely spaced sine waves

Uniform, Hamming

Excitation signals (hammer blow)

Force

Response signals

Exponential

Unknown content

Hanning

Initially, you might not have enough information about the signal to select the most appropriate smoothing window for the signal. You might need to experiment with different smoothing windows to find the best one. Always compare the performance of different smoothing windows to find the best one for the application.