High Precision Localisation with Dual-Constellation for Railway Applications

Gehrt, Jan-Jöran; Konrad, Thomas; Lin, Jiaying; Breuer, M.; Abel, Dirk; Zweigel, René

doi:10.33012/2018.15570

Cited by 5 publications

(2 citation statements)

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“…In a preprocessing step, differential corrections are calculated using pseudoranges from a reference station received via a modem, implemented in Nitsch et al (2021). If no correction data is available (e.g., during network connection outages), the correction method is replaced by dual-frequency methods or model-based methods, explained in more detail in Gehrt et al (2018). Further steps in preprocessing are the calculation of satellite positions and velocities as the tightly coupled navigation filter needs them.…”

Section: Gnss Preprocessingmentioning

confidence: 99%

“…The publication on hand describes the further development of a tightly coupled navigation filter presented in former publications (Breuer et al, 2016;Gehrt et al, 2018;Konrad et al, 2018). It is part of the development of the Autonomes Robustes Transportsystem für hybride Umweltschonende Rohstoffgewinnung auf basis knickgelenker Sonderfahrzeuge (ARTUS) research project, in which an autonomous transport fleet is being developed for use in hybrid mines.…”

Section: Introductionmentioning

confidence: 99%

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Speed Sensor-Aided Navigation Filter for Robust Localization in GNSS-Denied Mining Environments

Benz

Gehrt

Zweigel

et al. 2023

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The automation of mining haulage vehicles has great potential in terms of safety and economy. The performance of autonomous vehicles depends largely on highly accurate vehicle state information. Deep mines are especially challenging, as satellite-based localization methods are reaching their limits. Therefore, we introduce a new navigation filter concept for the precise and robust localization of the haulage fleet that can handle temporary GNSS interruptions in deep open-pit mines. The multi-sensor navigation filter utilizes an inertial measurement unit and is aided by GNSS. We introduce a new optical speed sensor update within the tightly coupled unscented Kalman filter. The speed sensor measures the slip-free two-dimensional speed above ground. The filter was validated with an articulated dumper in a gravel pit. The new filter achieved a mean position error of 0.24 m during a test drive of 190 s with a simulated GNSS outage of 90 s.

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Section: Gnss Preprocessingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%