Multisensor modeling underwater with uncertain information
Citable URI
https://hdl.handle.net/1912/4809DOI
10.1575/1912/4809Keyword
Stochastic analysis; Scanning systemsAbstract
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.
Description
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 Citation
Thesis: Stewart, W. Kenneth, "Multisensor modeling underwater with uncertain information", 1988-07-05, DOI:10.1575/1912/4809, https://hdl.handle.net/1912/4809Related items
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