Gishkori, Shahzad; Daniel, Liam; Gashinova, Marina; Mulgrew, Bernard. (2018). Imaging for a Forward Scanning Automotive Synthetic Aperture Radar, [dataset]. The University of Edinburgh. The School of Engineering. Institute for Digital Communications. https://doi.org/10.7488/ds/2440.
Data supporting the publication: Gishkori, S, Daniel, L, Gashinova, M & Mulgrew, B 2018, 'Imaging for a Forward Scanning Automotive Synthetic Aperture Radar' IEEE Transactions on Aerospace and Electronic Systems. DOI: 10.1109/TAES.2018.2871436. In this paper, we propose a forward scanning synthetic aperture radar methodology for a forward-looking automotive (low-terahertz) radar which combines scene scanning with synthetic aperture processing, resulting in enhanced angular resolution and improved imaging. We propose two algorithms: i) a modified back-projection algorithm, and ii) a compressed sensing based back-projection algorithm. We suggest techniques to reduce computational complexity of the proposed algorithms. Results of simulation and real-data experiments corroborate the validity of our proposed methodology and algorithms.
The data (real-data) contains three files. The two .mat files contain data and the .m file is the matlab code. Running the matlab code by loading one of the data files generates a basic radar image. The paper basically uses this data to test our proposed methods.
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