Note: This page has been translated by MathWorks. Please click here

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

High-resolution FFT of a portion of a spectrum

**Library:**DSP System Toolbox / Transforms

The Zoom FFT block computes the fast Fourier Transform (FFT) of a
signal over a portion of frequencies in the Nyquist interval. By setting an appropriate
decimation factor *D*, and sampling rate *Fs*, you can
choose the bandwidth of frequencies to analyze *BW*, where
*BW* = *Fs*/*D*. You can also
select a specific range of frequencies to analyze in the Nyquist interval by choosing
the center frequency of the desired band.

The resolution of a signal is the ratio of *Fs* and the FFT length
(*L*). Using zoom FFT, you can retain the same resolution you would
achieve with a full-size FFT on your original signal by computing a small FFT on a
shorter signal. The shorter signal comes from decimating the original signal. The
savings come from being able to compute a much shorter FFT while achieving the same
resolution. For a decimation factor of *D*, the new sampling rate,
*Fsd*, is *Fs*/*D*, and the new
frame size (and FFT length) is *Ld* =
*L*/*D*. The resolution of the decimated signal is
*Fsd*/*Ld* =
*Fs*/*L*. To achieve a higher resolution of the
shorter band, use the original FFT length, *L*, instead of the
decimated FFT length, *Ld*.

The zoom FFT algorithm leverages bandpass filtering before computing the FFT of the signal.
The concept of bandpass filtering is that suppose you are interested in the
band [*F1*, *F2*] of the original input
signal, sampled at the rate *Fs* Hz. If you pass this
signal through a complex (one-sided) bandpass filter centered at
*Fc* =
(*F1*+*F2*)/2, with the
bandwidth *BW* = *F2* –
*F1*, and then downsample the signal by a
factor of *D* =
floor(*Fs*/*BW*), the desired
band comes down to the baseband.

If *Fc* cannot be expressed in the form of
*k*×*Fs*/*D*, where
*k* is an integer, then the shifted, decimated spectrum is not centered
at DC. In this case, the center frequency gets translated to *Fd*.

$${F}_{d}={F}_{c}-({F}_{s}/D)\times floor((D\times {F}_{c}+{F}_{s}/2)/{F}_{s})$$

The complex bandpass filter is obtained by first designing a lowpass filter prototype and then multiplying the lowpass coefficients with a complex exponential. This algorithm uses a multirate, multistage FIR filter as the lowpass filter prototype. To obtain the bandpass filter, the coefficients of each stage are frequency shifted. The decimation factor is the cumulative decimation factor of each stage. The complex bandpass filter followed by the decimator are implemented using an efficient polyphase structure. For more details on the design of the complex bandpass filter from the multirate multistage FIR filter prototype, see Zoom FFT and Complex Bandpass Filter Design.

[1] Harris, F.J. *Multirate Signal Processing for Communication
Systems*. Prentice Hall, 2004, pp. 208–209.

`dsp.DCT`

|`dsp.FFT`

|`dsp.HDLFFT`

|`dsp.HDLIFFT`

|`dsp.IDCT`

|`dsp.IFFT`

|`dsp.ZoomFFT`

Was this topic helpful?