Using negative information to improve performance of forward scatter arrays

Abstract

Many tracking algorithms, such as implementations or Kalman filters, use only target positioning data as input. They ignore negative information from sensors that do not detect the target. Recent improvements in computing performance allow the development of tracking algorithms that can fuse information from many sources, including negative information, into the target motion analysis. This thesis evaluates th significance of negative information in a discrete tracking algorithm applied to a tracking scenario in which an array of forward scatter tripwire sensors covers the search area. Additionally, this thesis explores the effect of selected arrangements of an array of tripwire sensors and performance parameters on tracking capability. Using negative information significantly improves tracking performance, especially in a cost-effective arrangement of tripwires where several lines of position are coincident.