Fransiska, Enggar and Muthiah, Annisa Maulidary and Winarko, Oktanto Dedi and Samijayani, Octarina Nur and Rahmatia, Suci (2017) Performance comparison of various windowing on FMCW radar signal processing. In: 2016 International Symposium on Electronics and Smart Devices (ISESD). Institute of Electrical and Electronics Engineers, Bandung, pp. 326-330. ISBN 978-1-5090-3840-4
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Abstract
This paper discusses signal processing of FMCW radar. Signal processing was done to translate the signal from the time domain to distance estimation and optimization of defining the target using windowing. Blackmann, Hamming, Hanning, and Bartlet are the types of windowing used in this research. We offer the new method for windowing by separating the data in near and far distance. We suppress the signal from short distance and strengthen the signal in far distance. Signal processing was done by an algorithm to test the suitability of the furthest distance and to compare the result of signal processing using different types of window. The algorithm is used to combine complex data I and Q then apply windowing, and FFT the signal to take the range of target. Based on the algorithm, we present a comparison of signal processing using different windowing with regular windowing and new method to detect the farthest distance from the target detectable by radar, 70.896 km or 38 nautical miles (nmi).
Item Type: | Book Section |
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Additional Information: | Presentedn in The 2016 International Symposium on Electronics and Smart Devices (ISESD) on 29-30 November 2016 in Bandung, Indonesia. |
Uncontrolled Keywords: | Doppler radar; Signal processing algorithms; Frequency modulation; Radar signal processing; Frequency-domain analysis |
Subjects: | 600 Applied sciences & technology > 620 Engineering 600 Applied sciences & technology > 620 Engineering > 621 Applied Physics |
Divisions: | Universitas Al-Azhar Indonesia (UAI) > Fakultas Sains dan Teknologi (FST) > Teknik Elektro |
Depositing User: | Rifda Jilan |
Date Deposited: | 04 Nov 2021 08:23 |
Last Modified: | 19 Jun 2022 23:25 |
URI: | http://eprints.uai.ac.id/id/eprint/1739 |
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