Accession Number : ADA339011

Title :   Application of Bayesian Networks to Midcourse Multi-Target Tracking

Corporate Author : LOCKHEED MARTIN MISSILES AND SPACE CO SUNNYVALE CA

Personal Author(s) : Kovacich, Michael

PDF Url : ADA339011

Report Date : 03 AUG 1989

Pagination or Media Count : 88

Abstract : This presentation discusses the application of Bayesian Networks or Influence Diagrams to the implementation of midcourse tracking algorithms. The Influence Diagram is used to represent and manipulate probabilistic information in complex networks of random variables. The generic capabilities of the Influence Diagram are used to carry out eh major tracking functions, including linear gaussian state estimation, data association hypothesis scoring and track promotion scoring.

Descriptors :   *NEURAL NETS, *TARGET DETECTION, DATA BASES, ALGORITHMS, RANDOM VARIABLES, STATISTICAL INFERENCE, MULTIPLE TARGETS, BAYES THEOREM, MIDCOURSE GUIDANCE.

Subject Categories : Cybernetics
      Target Direction, Range and Position Finding
      Miscellaneous Detection and Detectors

Distribution Statement : APPROVED FOR PUBLIC RELEASE