Sensor Management with Regional Statistics for the PHD Filter

Marian Andrecki, Emmanuel D Delande, Jeremie Houssineau, Daniel E Clark

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

4 Citations (Scopus)

Abstract

This paper investigates a sensor management scheme that aims at minimising the regional variance in the number of objects present in regions of interest whilst performing multi-target filtering with the PHD filter. The experiments are conducted in a simulated environment with groups of targets moving through a scene in order to inspect the behaviour of the manager. The results demonstrate that computing the variance in the number of objects in different regions provides a viable means of increasing situational awareness where complete coverage is not possible. A discussion follows, highlighting the limitations of the PHD filter and discussing the applicability of the proposed method to alternative available approaches in multi-object filtering.

Original languageEnglish
Title of host publication2015 Sensor Signal Processing for Defence (SSPD)
PublisherIEEE
ISBN (Print)9781479974443
DOIs
Publication statusPublished - 2015
Event5th Sensor Signal Processing for Defence 2015 - Edinburgh, United Kingdom
Duration: 9 Sep 201510 Sep 2015

Conference

Conference5th Sensor Signal Processing for Defence 2015
Abbreviated titleSSPD 2015
Country/TerritoryUnited Kingdom
CityEdinburgh
Period9/09/1510/09/15

ASJC Scopus subject areas

  • Signal Processing
  • Instrumentation

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