Frequency domain image reconstruction algorithms offer significant advantages, especially for applications for which the reconstruction time is crucial. In the frequency domain, image reconstruction can be realized using fast Fourier transformations, reducing the complexity and thus the execution time of the reconstruction algorithm. In this paper, we adopt range migration techniques to reconstruct radar images from numerical and experimental data. The aim is to examine the robustness of the range migration algorithm (RMA) as a function of sampling sparsity under varying noise levels. Considering that sampling at Nyquist rates can be quite challenging for the conventional synthetic aperture radar (SAR) acquisition, we investigate the behavior of the reconstruction algorithm for larger sampling steps.