Comparison of Simple DME/DME Positioning Method and Augmentation Using Extended Kalman Filtering, Unscented Kalman Filtering and Particle Filtering
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F24%3A00537163" target="_blank" >RIV/60162694:G43__/24:00537163 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1109/DASC43569.2019.9081811" target="_blank" >http://dx.doi.org/10.1109/DASC43569.2019.9081811</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/DASC43569.2019.9081811" target="_blank" >10.1109/DASC43569.2019.9081811</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Comparison of Simple DME/DME Positioning Method and Augmentation Using Extended Kalman Filtering, Unscented Kalman Filtering and Particle Filtering
Popis výsledku v původním jazyce
Modern air navigation is primarily based on FMS performance. Navigation with RNP and real time data processing, in areas with high air traffic density, would be very difficult without this type of system. These systems use selected types of navigation modes depending on the type of used signal sources. Selected FMSs and navigation modes apply filters that further improve the resulting position estimates. The most well-known type of the filter is Kalman Filter, which is widely implemented in GNSS receivers. At the same time, this type of filter is also used to create the resulting position based on a combination of two navigation sources, such as GNSS/INS. Another navigation method, among other also used for making a backup of the GNSS system, uses the DME ground beacon network and the FMS navigation method is called DME/DME. The DME/DME navigation is often not associated with selecting filter type to improve the resulting position estimate. This paper compares the designed simple DME/DME navigation method and the augmented ones, using Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and less known Particle Filter (PF). The analyzed methods are evaluated for their resulting position estimate accuracy and for statistical indicators. The simulations are based on the data obtained from on-board Mi-17 helicopter recorders and are compared to the actual indicated GPS positions. Slant-range distances used in the simulations are obtained from the designed DME beacon network, which corresponds to the actual location of the beacons in the Czech Republic and neighboring countries.
Název v anglickém jazyce
Comparison of Simple DME/DME Positioning Method and Augmentation Using Extended Kalman Filtering, Unscented Kalman Filtering and Particle Filtering
Popis výsledku anglicky
Modern air navigation is primarily based on FMS performance. Navigation with RNP and real time data processing, in areas with high air traffic density, would be very difficult without this type of system. These systems use selected types of navigation modes depending on the type of used signal sources. Selected FMSs and navigation modes apply filters that further improve the resulting position estimates. The most well-known type of the filter is Kalman Filter, which is widely implemented in GNSS receivers. At the same time, this type of filter is also used to create the resulting position based on a combination of two navigation sources, such as GNSS/INS. Another navigation method, among other also used for making a backup of the GNSS system, uses the DME ground beacon network and the FMS navigation method is called DME/DME. The DME/DME navigation is often not associated with selecting filter type to improve the resulting position estimate. This paper compares the designed simple DME/DME navigation method and the augmented ones, using Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and less known Particle Filter (PF). The analyzed methods are evaluated for their resulting position estimate accuracy and for statistical indicators. The simulations are based on the data obtained from on-board Mi-17 helicopter recorders and are compared to the actual indicated GPS positions. Slant-range distances used in the simulations are obtained from the designed DME beacon network, which corresponds to the actual location of the beacons in the Czech Republic and neighboring countries.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
20304 - Aerospace engineering
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2019
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
IEEE-AIAA Digital Avionics Systems Conference
ISBN
978-1-7281-0649-6
ISSN
2155-7195
e-ISSN
—
Počet stran výsledku
6
Strana od-do
—
Název nakladatele
Institute of Electrical and Electronics Engineers Inc.
Místo vydání
San Diego, California, USA
Místo konání akce
San Diego, United States of America
Datum konání akce
8. 9. 2019
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000588253200197