Fast Interpolation of Complex Baseband Signals

This contribution contains 3 custom and easy to use interpolation routines that outperform the matlab functions resample.m and interp.m.


Updated 31 Dec 2021

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I provide 3 new interpolation (by a K factor) routines:
  1. interp11.m is fast-convolution based and basically convolves the input signal with a sinc window.
  2. interp21.m is based on zero-padding in the frequency domain.
  3. interp31.m is a more elaborate zero-padding technique originating from a SAR Signal Processing book by professor M. Soumekh.
The following assumptions were made:
  1. All input signals should be of even length, preferrably a power of 2.
  2. All input signals should be in baseband.
  3. The first sample x(1) corresponds to x[0].
It has been proven that for the provided chirp signal, all three routines run faster than matlab-provided routines resample.m and interp.m
Also, it has been proven that interp11.m is also the most accurate of all.
Run the interpdemo5.m to see the results.
Note: The interpolation is not performed on a given grid but is based on a factor K. This means that if the length of input signal x is Lx, the length of the output signal y will be Ly=K*Lx.

Cite As

Ilias Konsoulas (2023). Fast Interpolation of Complex Baseband Signals (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
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Version Published Release Notes

I deleted some redundant files to avoid confusion.