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Neural Networks Application for Processing of the Data from the FMICW Radars

1
Faculty of Electrical Engineering and Informatics, University of Pardubice, 532 10 Pardubice, Czech Republic
2
Wireless Communications Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam
*
Author to whom correspondence should be addressed.
Symmetry 2019, 11(10), 1308; https://doi.org/10.3390/sym11101308
Received: 5 September 2019 / Revised: 23 September 2019 / Accepted: 9 October 2019 / Published: 17 October 2019
In this paper the results of the Neural Networks and machine learning applications for radar signal processing are presented. The radar output from the primary radar signal processing is represented as a 2D image composed from echoes of the targets and noise background. The Frequency Modulated Interrupted Continuous Wave (FMICW) radar PCDR35 (Portable Cloud Doppler Radar at the frequency 35.4 GHz) was used. Presently, the processing is realized via a National Instruments industrial computer. The neural network of the proposed system is using four or five (optional for the user) signal processing steps. These steps are 2D spectrum filtration, thresholding, unification of the target, target area transforming to the rectangular shape (optional step), and target board line detection. The proposed neural network was tested with sets of four cases (100 tests for every case). This neural network provides image processing of the 2D spectrum. The results obtained from this new system are much better than the results of our previous algorithm. View Full-Text
Keywords: FMICW radar; radar signal analysis; neural network; 2D spectrum; image processing FMICW radar; radar signal analysis; neural network; 2D spectrum; image processing
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Rejfek, L.; N. Nguyen, T.; Chmelar, P.; Beran, L.; T. Tran, P. Neural Networks Application for Processing of the Data from the FMICW Radars. Symmetry 2019, 11, 1308.

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