Using a multiple analytical distribution filter for underwater localization

Dov Kruger, Hongyuan Shi, Yingying Chen, Hongbo Liu, Jie Yang, Len Imas

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

Abstract

This paper presents a high efficiency algorithm, Multiple Analytical Distribution Filter (MADF), to estimate location for underwater navigation. Using small grid sampling around candidate areas of high probability, MADF computes probabilities directly from the known analytical distributions of each beacon. The algorithm is deterministic and achieves similar results to particle filters, but at a lower computational cost in our tests. MADF and particle filters represent improvements over Kalman Filters for environments characterized by non-Gaussian noise distribution.

Original languageEnglish (US)
Title of host publicationUnmanned/Unattended Sensors and Sensor Networks VI
DOIs
StatePublished - 2009
Externally publishedYes
EventUnmanned/Unattended Sensors and Sensor Networks VI Conference - Berlin, Germany
Duration: Sep 1 2009Sep 3 2009

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7480
ISSN (Print)0277-786X

Other

OtherUnmanned/Unattended Sensors and Sensor Networks VI Conference
CountryGermany
CityBerlin
Period9/1/099/3/09

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Keywords

  • Localization
  • MADF
  • Particle filter
  • Underwater navigation

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