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Acoustic multipath identification with expectation-maximization

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5 Author(s)
Bingham, B. ; Massachusetts Inst. of Technol., Cambridge, MA, USA ; Mindell, D. ; Yoerger, D. ; Foley, B.
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Deep-sea autonomous positioning is susceptible to unmodeled measurement errors. Acoustic range measurements for long baseline navigation are not normally distributed, a situation that erodes the robustness and precision of estimation techniques. A mixed-distribution model captures the combination of direct-path, multipath, and spurious returns common for acoustic localization in limited-range survey. Expectation-Maximization concurrently identifies the parameters of the model and characterizes the observations, converging on a model for homogeneous instrumented environments. The resulting representation aids autonomous navigation for precision applications.

Published in:

OCEANS 2003. Proceedings  (Volume:5 )

Date of Conference:

22-26 Sept. 2003