Iterated Extended Kalman Filter with Implicit Measurement Equation and Nonlinear Constraints for Information-Based Georeferencing

authored by: Sören Vogel, Hamza Alkhatib, Ingo Neumann
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.
Organisation(s): Geodetic Institute
Type: Conference contribution
Pages: 1209-1216
No. of pages: 8
Publication date: 05.09.2018
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Computer Vision and Pattern Recognition, Signal Processing, Statistics, Probability and Uncertainty, Instrumentation
Electronic version(s): https://doi.org/10.23919/icif.2018.8455258 (Access: Closed)
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