Details
| Original language | English |
|---|---|
| Title of host publication | 2018 21st International Conference on Information Fusion, FUSION 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1209-1216 |
| Number of pages | 8 |
| ISBN (print) | 9780996452762 |
| Publication status | Published - 5 Sept 2018 |
| Event | 21st International Conference on Information Fusion, FUSION 2018 - Cambridge, United Kingdom (UK) Duration: 10 Jul 2018 → 13 Jul 2018 |
Abstract
Accurate, reliable and complete georeferencing with kinematic multi-sensor systems (MSS) is very demanding if common types of observations (e.g. usually GNSS) are imprecise or completely absence. The main reasons for this are challenging areas of indoor applications or inner-city areas with shadowing and multipath effects. However, those complex and tough environments are rather the rule than the exception. Consequently, we are developing an information-based georeferencing approach which can still estimate precise and accurate pose parameters when other current methods may fail. We modified an iterated extended Kalman filter (IEKF) approach which can deal with implicit measurement equations and introduced nonlinear equality constraints for the state parameters to integrate additional information. Hence, we can make use of geometric circumstances in the direct environment of the MSS and provide a more precise and reliable georeferencing.
Keywords
- 6-DOF, georeferencing, IEKF, implicit model, multi-sensor systems, nonlinear constraints
ASJC Scopus subject areas
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Computer Science(all)
- Signal Processing
- Decision Sciences(all)
- Statistics, Probability and Uncertainty
- Physics and Astronomy(all)
- Instrumentation
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2018 21st International Conference on Information Fusion, FUSION 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1209-1216 8455258.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Iterated Extended Kalman Filter with Implicit Measurement Equation and Nonlinear Constraints for Information-Based Georeferencing
AU - Vogel, Sören
AU - Alkhatib, Hamza
AU - Neumann, Ingo
N1 - Funding Information: This work was funded by the German Research Foundation (DFG) as part of the Research Training Group i.c.sens [RTG 2159] and NE 1453/5-1. Publisher Copyright: © 2018 ISIF Copyright: Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/9/5
Y1 - 2018/9/5
N2 - Accurate, reliable and complete georeferencing with kinematic multi-sensor systems (MSS) is very demanding if common types of observations (e.g. usually GNSS) are imprecise or completely absence. The main reasons for this are challenging areas of indoor applications or inner-city areas with shadowing and multipath effects. However, those complex and tough environments are rather the rule than the exception. Consequently, we are developing an information-based georeferencing approach which can still estimate precise and accurate pose parameters when other current methods may fail. We modified an iterated extended Kalman filter (IEKF) approach which can deal with implicit measurement equations and introduced nonlinear equality constraints for the state parameters to integrate additional information. Hence, we can make use of geometric circumstances in the direct environment of the MSS and provide a more precise and reliable georeferencing.
AB - Accurate, reliable and complete georeferencing with kinematic multi-sensor systems (MSS) is very demanding if common types of observations (e.g. usually GNSS) are imprecise or completely absence. The main reasons for this are challenging areas of indoor applications or inner-city areas with shadowing and multipath effects. However, those complex and tough environments are rather the rule than the exception. Consequently, we are developing an information-based georeferencing approach which can still estimate precise and accurate pose parameters when other current methods may fail. We modified an iterated extended Kalman filter (IEKF) approach which can deal with implicit measurement equations and introduced nonlinear equality constraints for the state parameters to integrate additional information. Hence, we can make use of geometric circumstances in the direct environment of the MSS and provide a more precise and reliable georeferencing.
KW - 6-DOF
KW - georeferencing
KW - IEKF
KW - implicit model
KW - multi-sensor systems
KW - nonlinear constraints
UR - http://www.scopus.com/inward/record.url?scp=85050637709&partnerID=8YFLogxK
U2 - 10.23919/icif.2018.8455258
DO - 10.23919/icif.2018.8455258
M3 - Conference contribution
AN - SCOPUS:85050637709
SN - 9780996452762
SP - 1209
EP - 1216
BT - 2018 21st International Conference on Information Fusion, FUSION 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st International Conference on Information Fusion, FUSION 2018
Y2 - 10 July 2018 through 13 July 2018
ER -