SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

Sensor Scheduling And Target Tracking Using Expectation Propagation

Author(s)

Travis Hestilow	University of Texas at San Antonio
Tao Wei	University of Texas at San Antonio
Yufei Huang	University of Texas at San Antonio

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Abstract

Multiple-sensor scheduling for target tracking applications using expectation propagation (EP) is examined. The method is an alternative to that of [1] wherein an Extended Kalman Filter (EKF) was used to predict the next state for sensor scheduling purposes, and a sequential Monte Carlo particle filter (PF) method was used to implement the target tracking. In this application, EP is used instead of PF to estimate the unobserved state variable. Initial simulations show the EKF+EP (w/scheduling) algorithm performs at least as well as EKF+PF, with a shorter run time and less programmatic complexity. EKF+EP (w/scheduling) also performs better than EKF+EP (w/o scheduling).