Skip to main navigation Skip to search Skip to main content

Cost-reference particle filters and fusion of information

  • Universidad Carlos III de Madrid

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Cost-reference particle filtering is a methodology for tracking unknowns in a system without reliance on probabilistic information about the noises in the system. The methodology is based on analogous principles as the ones of standard particle filtering. Unlike the random measures of standard particle filters that are composed of particles and weights, the random measures of cost-reference particle filters contain particles and user-defined costs. In this paper, we discuss a few scenarios where we need to meld random measures of two or more cost-reference particle filters. The objective is to obtain a fused random measure that combines the information from the individual cost-reference particle filters.

Original languageEnglish
Title of host publication2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings
Pages286-291
Number of pages6
DOIs
StatePublished - 2009
Event2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009 - Marco Island, FL, United States
Duration: Jan 4 2009Jan 7 2009

Publication series

Name2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings

Conference

Conference2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009
Country/TerritoryUnited States
CityMarco Island, FL
Period01/4/0901/7/09

Keywords

  • Costs
  • Distributed processing
  • Fusion
  • Particle filtering

Fingerprint

Dive into the research topics of 'Cost-reference particle filters and fusion of information'. Together they form a unique fingerprint.

Cite this