Development of FMCW Radar Signal Processing for High-Speed Railway Collision Avoidance
| Autor: | Farra Anindya Putri, Dayat Kurniawan, Rahmawati Hasanah, Taufiqurrahman Taufiqurrahman, Eko Joni Pristianto, Hana Arisesa, Yusuf Nur Wijayanto, Deni Permana, Winy Desvasari, Ken Paramayudha, Arief Budi Santiko, Dadin Mahmudin, Pamungkas Daud, Fajri Darwis, Erry Dwi Kurniawan, Arie Setiawan, Tajul Miftahushudur, Prasetyo Putranto, Syamsu Ismail |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Jurnal Elektronika dan Telekomunikasi, Vol 22, Iss 1, Pp 40-47 (2022) |
| Druh dokumentu: | article |
| ISSN: | 1411-8289 2527-9955 |
| DOI: | 10.55981/jet.482 |
| Popis: | Collision is the main issue in safe transportation, including in the railway system. Sensor systems have been developed to detect obstacles to prevent a collision, such as using cameras. One disadvantage of the camera systems is that performance detection decreases in a not clean environment, like the target position behind the fogs. This paper discusses the development of frequency modulated continuous wave (FMCW) radar signal processing for high-speed railway collision avoidance. The development of radar signal processing combines a two-dimensional constant false alarm rate (2D-CFAR) and robust principal component analysis (RPCA) to detect moving targets under clutter. Cell average (CA) and Greatest of CA (GOCA) CFAR are evaluated under a cluttered wall environment along the railway track. From the experiment, the development of FMCW radar can detect stationary or moving obstacles around 675 meters in front of the locomotive. Combining 2D-CFAR and RPCA algorithm outperforms average background subtraction in extracting moving targets from strong clutter signals along the railway track. |
| Databáze: | Directory of Open Access Journals |
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