Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/70164
Title: Towards total kalman filtering for mobile mapping
Authors: Schaffrin, B
Iz, HB 
Issue Date: 2007
Publisher: Copernicus GmbH
Source: International archives in photogrammetry, remote sensing and the spatial information sciences, 2007, v. XXXVI-5/C55, 6 pages How to cite?
Journal: International archives of the photogrammetry, remote sensing and spatial information sciences 
Abstract: A dynamic model is the usual modus operandi of a Mobile Mapping System. The model solution, after linearization and discretization, is achieved using the Weighted Least-Squares (WLS) approach, which results in one of the various Kalman filter algorithms. However, implicit in the formulation is that neither the observation equation matrices nor the transition matrices at any epoch contain random entries. As such an assumption cannot always be guaranteed, we here allow random observational errors to enter the respective matrices. We replace the WLS by the Total-Least-Squares (TLS) principle - with or without weights - and apply it to this novel Dynamic Errors-in-Variables (DEIV) model, which results in what we call Total Kalman Filter (TKF). It promises to offer more representative solutions to the dynamic models of Mobile Mapping Systems over existing versions of Kalman filtering.
Description: 5th International Symposium on Mobile Mapping Technology, 2007, Padua, Italy, 29-31 May 2007
URI: http://hdl.handle.net/10397/70164
ISSN: 1682-1750
EISSN: 2194-9034
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

16
Last Week
0
Last month
Citations as of Feb 25, 2018

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.