We present the main assumptions about the algorithmization of the analysis of measurement data recorded in mobile satellite measurements. The research team from the Gda´nsk University of Technology and the Maritime University in Gdynia, as part of a research project conducted in cooperation with PKP PLK (Polish Railway Infrastructure Manager), developed algorithms supporting the identification and assessment of track axis layout. This article presents selected issues concerning the identification of a tramway line’s axis system. For this purpose, the supporting algorithm was developed and measurement data recorded using Global Navigation Satellite System (GNSS) techniques was evaluated and analyzed. The discussed algorithm identifies main track directions from multi-device data and repeated position recordings. In order to observe the influence of crucial factors, the investigated route was carefully selected. The chosen tramway track was characterized by its location in various field conditions and a diversified and complex geometric layout. The analysis of the obtained results was focused on the assessment of the signal’s dispersion and repeatability using residuals in relation to the estimated track’s direction. The presented methodology is intended to support railway infrastructure management processes, mainly in planning and maintenance through an effcient inventory of the infrastructure in service.
Authors
- dr hab. inż. Andrzej Wilk link open in new tab ,
- Cezary Specht,
- prof. dr hab. inż. Władysław Koc link open in new tab ,
- dr hab. inż. Krzysztof Karwowski link open in new tab ,
- dr hab. inż. Jacek Skibicki link open in new tab ,
- dr inż. Jacek Szmagliński link open in new tab ,
- dr hab. inż. Piotr Chrostowski link open in new tab ,
- dr inż Pawel S. Dabrowski,
- dr inż. Mariusz Specht,
- dr inż. Marek Zienkiewicz link open in new tab ,
- dr inż. Sławomir Judek link open in new tab ,
- mgr inż. Marcin Skóra,
- dr inż. Sławomir Grulkowski link open in new tab
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.3390/s20164408
- Category
- Publikacja w czasopiśmie
- Type
- artykuły w czasopismach
- Language
- angielski
- Publication year
- 2020