SDA Operator’s Manual
SDA-OM-E Rev H 201
Window Frequency Domain Parameters
Window Type
Highest Side
Lobe
(dB)
Scallop Loss
(dB)
ENBW
(bins)
Coherent Gain
(dB)
Rectangular
-13 3.92 1.0 0.0
Hanning (Von Hann)
-32 1.42 1.5 -6.02
Hamming
-43 1.78 1.37 -5.35
Flattop
-44 0.01 2.96 -11.05
Blackman–Harris
-67 1.13 1.71 -7.53
• ENBW - Equivalent Noise BandWidth (ENBW) is the bandwidth of a rectangular filter (same
gain at the center frequency), equivalent to a filter associated with each frequency bin, which
would collect the same power from a white noise signal. In the table on the previous page,
the ENBW is listed for each window function implemented, given in bins.
• Filters - Computing an N-point FFT is equivalent to passing the time-domain input signal
through N/2 filters and plotting their outputs against the frequency. The spacing of filters is
Delta f = 1/T, while the bandwidth depends on the window function used (see Frequency
Bins).
• Frequency Bins - The FFT algorithm takes a discrete source waveform, defined over N
points, and computes N complex Fourier coefficients, which are interpreted as harmonic
components of the input signal.
For a real source waveform (imaginary part equals 0), there are only N/2 independent
harmonic components.
An FFT corresponds to analyzing the input signal with a bank of N/2 filters, all having the
same shape and width, and centered at N/2 discrete frequencies. Each filter collects the
signal energy that falls into the immediate neighborhood of its center frequency. Thus it can
be said that there are N/2 "frequency bins."
The distance in hertz between the center frequencies of two neighboring bins is always:
Delta f = 1/T
Where T is the duration of the time-domain record in seconds.
The width of the main lobe of the filter centered at each bin depends on the window function
used. The rectangular window has a nominal width at 1.0 bin. Other windows have wider
main lobes (see table).
• Frequency Range - The range of frequencies computed and displayed is 0 Hz (displayed at
the left-hand edge of the screen) to the Nyquist frequency (at the rightmost edge of the
trace).
• Frequency Resolution - In a simple sense, the frequency resolution is equal to the bin width
Delta f. That is, if the input signal changes its frequency by Delta f, the corresponding
spectrum peak will be displaced by Df. For smaller changes of frequency, only the shape of
the peak will change.
However, the effective frequency resolution (that is, the ability to resolve two signals whose
frequencies are almost the same) is further limited by the use of window functions. The
ENBW value of all windows other than the rectangular is greater than Delta f and the bin
To Next Page
Loading...