Stewart W. Kenneth

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Stewart
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W. Kenneth
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  • Thesis
    Multisensor modeling underwater with uncertain information
    (Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 1988-07-05) Stewart, W. Kenneth
    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.
  • Technical Report
    A preliminary study of shallow-water sonar issues : signal motion loss and reverberation noise
    (Woods Hole Oceanographic Institution, 1993-09) Stewart, W. Kenneth ; Chu, Dezhang ; Tang, Xiaoou
    This preliminary investigation addresses key program elements for sonar sensing in a shallow-water environment to establish bounds on possible solutions and to reduce program uncertainty. The modeling and experimental program focuses on two issues - the potential degradation of sonar data due to signal masking by shallow-water reverberation and signal loss caused by extreme platform motions. The research program combines theoretical analysis, experimental validation in a shallow-water environment, and development of a computer model to explore parametric sensitivity. Results from an initial dock-side test show good agreement with the theoretical predictions. From the shallow-water experiments and acoustic modeling we conclude that: (1) Signal motion loss can influence the reverberation level significantly but is not the dominant factor in target detection for sonars in the frequency range of interest (>200 kHz); a high-quality (velocity-aided) inertial navigation and attitude system will be sufficient to correct for geometric distortions caused by platform motion. (2) Although surface reverberation and multipath noise can be a factor, partcularly in shadow-mode imaging, reverberation levels are rapidly attenuated at the frequencies of interest and beam patterns can be manipulated to reject most interferences; echo-mode imaging is still dominated by the contrast between target strength and bottom reverberation.