Details
| Original language | English |
|---|---|
| Article number | 2400 |
| Journal | Sensors (Switzerland) |
| Volume | 18 |
| Issue number | 7 |
| Early online date | 23 Jul 2018 |
| Publication status | Published - Jul 2018 |
Abstract
Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This is especially true for applications dealing with highly automatic or even autonomous driving. Subsequently, multi-sensor platforms including laser scanners and cameras, as well as map data are used to enhance the navigation performance, namely in accuracy, integrity, continuity and availability. Although well-established procedures for integrity monitoring exist for aircraft navigation, for sensors and fusion algorithms used in automotive navigation, these concepts are still lacking. The research training group i.c.sens, integrity and collaboration in dynamic sensor networks, aims to fill this gap and to contribute to relevant topics. This includes the definition of alternative integrity concepts for space and time based on set theory and interval mathematics, establishing new types of maps that report on the trustworthiness of the represented information, as well as taking advantage of collaboration by improved filters incorporating person and object tracking. In this paper, we describe our approach and summarize the preliminary results.
Keywords
- Camera, Collaboration, GNSS, Integrity, Interval mathematics, Laser scanner, Set theory
ASJC Scopus subject areas
- Chemistry(all)
- Analytical Chemistry
- Biochemistry, Genetics and Molecular Biology(all)
- Biochemistry
- Physics and Astronomy(all)
- Atomic and Molecular Physics, and Optics
- Physics and Astronomy(all)
- Instrumentation
- Engineering(all)
- Electrical and Electronic Engineering
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In: Sensors (Switzerland), Vol. 18, No. 7, 2400, 07.2018.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Integrity and Collaboration in Dynamic Sensor Networks
AU - Schön, Steffen
AU - Brenner, Claus
AU - Alkhatib, Hamza
AU - Coenen, Max
AU - Dbouk, Hani
AU - Garcia-Fernandez, Nicolas
AU - Fischer, Colin
AU - Heipke, Christian
AU - Lohmann, Katja
AU - Neumann, Ingo
AU - Nguyen, Uyen
AU - Paffenholz, Jens André
AU - Peters, Torben
AU - Rottensteiner, Franz
AU - Schachtschneider, Julia
AU - Sester, Monika
AU - Sun, Ligang
AU - Vogel, Sören
AU - Voges, Raphael
AU - Wagner, Bernardo
N1 - Funding information: This work was funded by the German Research Foundation (DFG) as a part of the Research Training Group i.c.sens (GRK2159).
PY - 2018/7
Y1 - 2018/7
N2 - Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This is especially true for applications dealing with highly automatic or even autonomous driving. Subsequently, multi-sensor platforms including laser scanners and cameras, as well as map data are used to enhance the navigation performance, namely in accuracy, integrity, continuity and availability. Although well-established procedures for integrity monitoring exist for aircraft navigation, for sensors and fusion algorithms used in automotive navigation, these concepts are still lacking. The research training group i.c.sens, integrity and collaboration in dynamic sensor networks, aims to fill this gap and to contribute to relevant topics. This includes the definition of alternative integrity concepts for space and time based on set theory and interval mathematics, establishing new types of maps that report on the trustworthiness of the represented information, as well as taking advantage of collaboration by improved filters incorporating person and object tracking. In this paper, we describe our approach and summarize the preliminary results.
AB - Global Navigation Satellite Systems (GNSS) deliver absolute position and velocity, as well as time information (P, V, T). However, in urban areas, the GNSS navigation performance is restricted due to signal obstructions and multipath. This is especially true for applications dealing with highly automatic or even autonomous driving. Subsequently, multi-sensor platforms including laser scanners and cameras, as well as map data are used to enhance the navigation performance, namely in accuracy, integrity, continuity and availability. Although well-established procedures for integrity monitoring exist for aircraft navigation, for sensors and fusion algorithms used in automotive navigation, these concepts are still lacking. The research training group i.c.sens, integrity and collaboration in dynamic sensor networks, aims to fill this gap and to contribute to relevant topics. This includes the definition of alternative integrity concepts for space and time based on set theory and interval mathematics, establishing new types of maps that report on the trustworthiness of the represented information, as well as taking advantage of collaboration by improved filters incorporating person and object tracking. In this paper, we describe our approach and summarize the preliminary results.
KW - Camera
KW - Collaboration
KW - GNSS
KW - Integrity
KW - Interval mathematics
KW - Laser scanner
KW - Set theory
UR - http://www.scopus.com/inward/record.url?scp=85050629434&partnerID=8YFLogxK
U2 - 10.3390/s18072400
DO - 10.3390/s18072400
M3 - Article
C2 - 30041498
AN - SCOPUS:85050629434
VL - 18
JO - Sensors (Switzerland)
JF - Sensors (Switzerland)
SN - 1424-8220
IS - 7
M1 - 2400
ER -