Performance metric in closed-loop sensor management for stochastic populations

Emmanuel D. Delande, Jeremie Houssineau, Daniel E. Clark

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

2 Citations (Scopus)

Abstract

Methods for sensor control are crucial for modern surveillance and sensing systems to enable efficient allocation and prioritisation of resources. The framework of partially observed Markov decision processes enables decisions to be made based on data received by the sensors within an information-theoretic context. This work addresses the problem of closed-loop sensor management in a multi-target surveillance context where each target is assumed to move independently of other targets. Analytic expressions of the information gain are obtained, for a class of exact multi-target tracking filters are obtained and based on the Renyi divergence. The proposed method is sufficiently general to address a broad range of sensor management problems through the application-specific reward function defined by the operator.

Original languageEnglish
Title of host publicationSensor Signal Processing for Defence (SSPD), 2014
PublisherIEEE
Number of pages5
ISBN (Print)978-1-4799-5294-6
DOIs
Publication statusPublished - 31 Oct 2014
Event4th Sensor Signal Processing for Defence 2014 - Edinburgh, Edinburgh, United Kingdom
Duration: 8 Sep 20149 Sep 2014

Conference

Conference4th Sensor Signal Processing for Defence 2014
Abbreviated titleSSPD 2014
CountryUnited Kingdom
CityEdinburgh
Period8/09/149/09/14

ASJC Scopus subject areas

  • Signal Processing
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Delande, E. D., Houssineau, J., & Clark, D. E. (2014). Performance metric in closed-loop sensor management for stochastic populations. In Sensor Signal Processing for Defence (SSPD), 2014 [6943322] IEEE. https://doi.org/10.1109/SSPD.2014.6943322