RSFT: A realistic high dimensional sparse fourier transform and its application in radar signal processing
Shaogang Wang, Vishal M. Patel, Athina P. Petropulu · 2016
We propose a realistic high dimensional sparse Fourier transform (RSFT) algorithm, which detects frequencies in multidimensional data, provided that the data is sparse in the frequency domain. Although sparsity has been exploited before to reduce the complexity of the Discrete Fourier Transform, unlike previous approaches, the RSFT allows for off-grid frequencies. We provide a concrete application example on short range ubiquitous radar signal processing, and verify the feasibility of the RSFT in that scenario via simulations.