Cooperative localization of an acoustic using towed hydrophone arrays

Aditya S. Gadre, Darren K. Maczka, Davide Spinello, Brian R. McCarter, Daniel J. Stilwell, Wayne Neu, Michael J. Roan, John B. Hennage

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Scopus citations

Abstract

We describe field experiments in which a team of autonomous underwater vehicles cooperatively localize an acoustic source. The team implements a data fusion algorithm to enhance the localization performance of each individual vehicle and implements a decentralized motion control algorithm so that each vehicle maneuvers to minimize the joint localization error of the acoustic source. Each autonomous underwater vehicle is equipped with a custom-designed towed hydrophone array that measures the bearing angle between the array and the acoustic source. The noise statistics of the hydrophone arrays are state-dependent, and a generalized Kalman filter that accounts for the state-dependant measurement noise is utilized for localization.

Original languageEnglish (US)
Title of host publication2008 IEEE/OES Autonomous Underwater Vehicles, AUV 2008
DOIs
StatePublished - 2008
Event2008 IEEE/OES Autonomous Underwater Vehicles, AUV 2008 - Woods Hole, MA, United States
Duration: Oct 13 2008Oct 14 2008

Publication series

Name2008 IEEE/OES Autonomous Underwater Vehicles, AUV 2008

Conference

Conference2008 IEEE/OES Autonomous Underwater Vehicles, AUV 2008
Country/TerritoryUnited States
CityWoods Hole, MA
Period10/13/0810/14/08

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Electrical and Electronic Engineering

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