Multisensor modeling underwater with uncertain information
Stewart, W. Kenneth
MetadataShow full item record
This thesis develops an approach to the construction of multidimensional stochastic models for intelligent systems exploring an underwater environment. The important characteristics shared by such applications are: real-time constraints: unstructured, three-dimensional terrain; high-bandwidth sensors providing redundant, overlapping coverage; lack of prior knowledge about the environment; and inherent inaccuracy or ambiguity in sensing and interpretation. The models are cast as a three-dimensional spatial decomposition of stochastic, multisensor feature vectors that describe an underwater environment. Such models serve as intermediate descriptions that decouple low-level, high-bandwidth sensing from the higher-level, more asynchronous processes that extract information. A numerical approach to incorporating new sensor information--stochastic backprojection--is derived from an incremental adaptation of the summation method for image reconstruction. Error and ambiguity are accounted for by blurring a spatial projection of remote-sensor data before combining it stochastically with the model. By exploiting the redundancy in high-bandwidth sensing, model certainty and resolution are enhanced as more data accumulate. In the case of three-dimensional profiling, the model converges to a "fuzzy" surface distribution from which a deterministic surface map is extracted. Computer simulations demonstrate the properties of stochastic backprojection and stochastic models. Other simulations show that the stochastic model can be used directly for terrain-relative navigation. The method is applied to real sonar data sets from multibeam bathymetric surveying (Sea Beam), towed sidescan bathymetry (Sea MARC II), towed sidescan acoustic imagery (Sea MARC I & II), and high-resolution scanning sonar aboard a remotely operated vehicle. A multisensor application combines Sea Beam bathvmetry and Sea MARC I intensity models. Targeted real-time applications include shipboard mapping and survey, a piloting aid for remotely operated vehicles and manned submersibles, and world modeling for autonomous vehicles.
Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution July 5, 1988
Suggested CitationThesis: Stewart, W. Kenneth, "Multisensor modeling underwater with uncertain information", 1988-07-05, DOI:10.1575/1912/4809, https://hdl.handle.net/1912/4809
Showing items related by title, author, creator and subject.
Jasper, John P. (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 1988-05)The concentration and carbon isotopic composition (δ13C) of sedimentary organic carbon (Corg), N/C ratios, and terrigenous and marine δ13C-Corg end-members form a basis from which to address problems of Late Quaternary ...
Xu, Kevin (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 1999-09)An algorithm is developed for underwater acoustic signal processing with an array of hydrophones. With various acoustic signals coming from different directions, the maximum likelihood approach is used to estimate the ...
Fernandez, Vicente I. (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2011-06)The lateral line is a critical component of the fish sensory system, found to affect numerous aspects of behavior including maneuvering in complex fluid environments, schooling, prey tracking, and environment mapping. ...