23 May 2013 Subdimensional geo-localization from finite set statistics
Author Affiliations +
In practical circumstances, a problem that often occurs is to geo-localize an entity from surfacelevel imagery given wide area overhead information and other a priori information that might be used to relate the two views. Given a finite set of GMTI returns and surface-level imagery of a common region of space, we propose a statistical algorithm for the association of surface-level one-dimensional measurements of the finite set to entities of the shared-dimensional wide area overview. Specifically, the problem of fused tracking without reliable range information from a surface-level view of a subset of entities is solved by the association of projections of 3-dimensional movement and position measurements of the GMTI and surface-level imagery. In this process the position of the surface level observer is refined. We expand this algorithm to a set of surface level observers distributed over the region of interest and propose a system of continuous tracking of entities over congested areas. The fusion search algorithm exploits the invariant metric properties of projection in a matched-filter procedure as well as the partialordering of local apparent depth of objects. We achieve O(N) convergence thereby making this algorithm practical for large-N searches. The algorithm is demonstrated analytically and by simulation.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Frank Boyle, Frank Boyle, "Subdimensional geo-localization from finite set statistics", Proc. SPIE 8747, Geospatial InfoFusion III, 87470M (23 May 2013); doi: 10.1117/12.2019133; https://doi.org/10.1117/12.2019133

Back to Top