Accession Number:

ADA179437

Title:

A New Approach to Multitarget Tracking Using Probabilistic Data Association

Descriptive Note:

Technical rept.

Corporate Author:

ELECTRONICS RESEARCH LAB ADELAIDE (AUSTRALIA)

Personal Author(s):

Report Date:

1986-09-01

Pagination or Media Count:

33.0

Abstract:

This report develops the theory for a multitarget tracking algorithm based on Probabilistic Data Association with new selection rules for assigning sensor measurements to target track and for forming multitrack clusters. These new rules remove the requirement to form a gate about each targets predicted position for the selection of sensor measurements. The resultant algorithm is the same for all target tracks and clutter conditions. The algorithm adapts to the sensor measurements via probability terms which model the environment and sensor processing. Keywords Automatic tracking Kalman filtering Probability theory Probabilistic data association Estimation Australia.

Subject Categories:

  • Statistics and Probability
  • Active and Passive Radar Detection and Equipment

Distribution Statement:

APPROVED FOR PUBLIC RELEASE