Multisensor Modeling Underwater with Uncertain Information

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6980

Full metadata record

DC Field	Value	Language
dc.creator	Stewart, W. Kenneth, Jr.	-
dc.date	2004-10-20T20:12:07Z	-
dc.date	2004-10-20T20:12:07Z	-
dc.date	1988-07-01	-
dc.date.accessioned	2013-10-09T02:48:01Z	-
dc.date.available	2013-10-09T02:48:01Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AITR-1143	-
dc.identifier	http://hdl.handle.net/1721.1/6980	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	This thesis develops an approach to the construction of multidimensional stochastic models for intelligent systems exploring an underwater environment. It describes methods for building models by a three- dimensional spatial decomposition of stochastic, multisensor feature vectors. New sensor information is incrementally incorporated into the model by stochastic backprojection. Error and ambiguity are explicitly accounted for by blurring a spatial projection of remote sensor data before incorporation. The stochastic models can be used to derive surface maps or other representations of the environment. The methods are demonstrated on data sets from multibeam bathymetric surveying, towed sidescan bathymetry, towed sidescan acoustic imagery, and high-resolution scanning sonar aboard a remotely operated vehicle.	-
dc.format	17839255 bytes	-
dc.format	7028754 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AITR-1143	-
dc.title	Multisensor Modeling Underwater with Uncertain Information	-
Appears in Collections:	MIT Items

Files in This Item:

There are no files associated with this item.

DSpace JSPUI