Experimental analysis of a game-theoretic formulation of target tracking

DOI10.1016/j.automatica.2019.108793zbMath1441.93353OpenAlexW2998924509WikidataQ126347673 ScholiaQ126347673MaRDI QIDQ2173995

Yanbo Yang, Quan Pan, Simon Williams, William Moran, Xuezhi Wang, Timothy C. Brown

Publication date: 17 April 2020

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2019.108793

zbMATH Keywords

mutual informationPareto optimalitytarget trackingMarkov jump processfair game

Mathematics Subject Classification ID

Applications of game theory (91A80) Optimal stochastic control (93E20) Jump processes on discrete state spaces (60J74)

Related Items (1)

Finite‐time distributed block‐decomposed information filter for nonlinear systems with colored measurement noise

Cites Work

• On efficient sensor scheduling for linear dynamical systems
• Optimal sensor placement and motion coordination for target tracking
• On the efficiency of a bearings-only instrumental variable estimator for target motion analysis
• The interacting multiple model algorithm for systems with Markovian switching coefficients
• On the Use of Binary Programming for Sensor Scheduling
• Mobile Sensor Network Control Using Mutual Information Methods and Particle Filters
• Elements of Information Theory

This page was built for publication: Experimental analysis of a game-theoretic formulation of target tracking