Big_22.2_26.2_nf11_56x43cm_3mm_d9cm - is the radar data file; myfile_phi.txt - contains calibration coefficients for the phase linearization;
Main_Reconstruct_and_Proc.py - the main scipt with the code to read, process and visualize data with various options; Methods_Reconstruct_and_Proc.py - the script with all methods implementation.
-- Options: --
- read the data;
- apply Gaussian window with the specified widths stdx, stdy;
- apply high-pass/low-pass/band-pass Butterworth filtering to the data k-frequency spectrum;
- reconstruct a 3-D radar image with the FFT-based back-propagation method;
- (or reconstruct a radar image at a single frequency;)
- visualize the reconstructed data in xy/zx/zy planes, applying gamma-correction and choosing a colormap, axes numbers can be either physical mms or arrays indexes;
- (or visualize a single radar image;)
- move along the data slices with 'K' and 'J' keys.
- check whether the grids sampling satisfies the Nyquist and other criteria.
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For detailed information on radar image reconstruction see the classic work:
Sheen D.M., McMakin D.L., Hall T.E., “Three-dimensional millimeterwave imaging for concealed weapon detection,” IEEE Trans. Microwave Theory Tech., vol. 49, no. 9, pp. 1581–1592, Sep. 2001.
or its recent non-destructive testing application in our paper:
M. Chizh, A. Zhuravlev, V. Razevig and S. Ivashov, "Broadband Microwave Imaging for Foam Insulation Diagnostics," 2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama), Toyama, 2018, pp. 1887-1894. DOI: 10.23919/PIERS.2018.8598093