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Title: Towards total kalman filtering for mobile mapping
Authors: Schaffrin, B
Iz, HB 
Issue Date: 2007
Source: International archives in photogrammetry, remote sensing and the spatial information sciences, 2007, v. XXXVI-5/C55, 6 pages
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.
Publisher: Copernicus GmbH
Journal: International archives of the photogrammetry, remote sensing and spatial information sciences 
ISSN: 1682-1750
EISSN: 2194-9034
Description: 5th International Symposium on Mobile Mapping Technology, 2007, Padua, Italy, 29-31 May 2007
Appears in Collections:Conference Paper

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