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Gaussian Mixtures Proposal Density in Particle Filter for Track-Before-Detect

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F09%3A00502131" target="_blank" >RIV/49777513:23520/09:00502131 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Gaussian Mixtures Proposal Density in Particle Filter for Track-Before-Detect

  • Original language description

    The paper deals with state estimation for the track-before-detect approach using the particle lter. The focus is aimed at the track initiation proposal density of the particle lter which considerably affects estimate quality. The goal of the paper is todesign a proposal based on a Gaussian mixture using a bank of extended Kalman lters. This leads to root mean square error lower than that achieved by usual simple track initiation proposals. Due to application of several developed techniques reducing computational requirements of the designed proposal, the Gaussian mixture particle lter also achieves lower computational requirements than ordinary particle lter. Performance of the proposed Gaussian mixture track initiation proposal in the particle lter is demonstrated in a numerical example.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BC - Theory and management systems

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2009

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    FUSION: 2009 12TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4

  • ISBN

    978-0-9824-4380-4

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

  • Publisher name

    IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA

  • Place of publication

    NEW YORK

  • Event location

    Seattle, WA, USA

  • Event date

    Jul 9, 2009

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000273560000036