Extended Solution To Multiple Maneuvering Target Tracking

Yi-Nung Chung, D. L. Gustafson, E. Emre

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

An improved algorithm for tracking multiple maneuvering targets is presented. This approach is implemented with an approximate adaptive filter consisting of the 1-step conditional maximumlikelihood technique together with the extended Kalman filter and an adaptive maneuvering compensator. In order to avoid the extra computational burden of considering events with negligible probability, a validation matrix is defined in the tracking structure. Via this approach, both data association and target maneuvering problems can be solved simultaneously Detailed Monte-Carlo simulations of the algorithm for many tracking situations are described. Computer simulation results indicate that this approach successfully tracks multiple maneuvering targets over a wide range of conditions.

Original languageEnglish
Pages (from-to)876-887
Number of pages12
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume26
Issue number5
DOIs
Publication statusPublished - 1990 Jan 1

Fingerprint

Target tracking
Extended Kalman filters
Adaptive filters
Computer simulation
Monte Carlo simulation

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Electrical and Electronic Engineering

Cite this

@article{822072a39f434e149f9170111d40fd89,
title = "Extended Solution To Multiple Maneuvering Target Tracking",
abstract = "An improved algorithm for tracking multiple maneuvering targets is presented. This approach is implemented with an approximate adaptive filter consisting of the 1-step conditional maximumlikelihood technique together with the extended Kalman filter and an adaptive maneuvering compensator. In order to avoid the extra computational burden of considering events with negligible probability, a validation matrix is defined in the tracking structure. Via this approach, both data association and target maneuvering problems can be solved simultaneously Detailed Monte-Carlo simulations of the algorithm for many tracking situations are described. Computer simulation results indicate that this approach successfully tracks multiple maneuvering targets over a wide range of conditions.",
author = "Yi-Nung Chung and Gustafson, {D. L.} and E. Emre",
year = "1990",
month = "1",
day = "1",
doi = "10.1109/7.102720",
language = "English",
volume = "26",
pages = "876--887",
journal = "IEEE Transactions on Aerospace and Electronic Systems",
issn = "0018-9251",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "5",

}

Extended Solution To Multiple Maneuvering Target Tracking. / Chung, Yi-Nung; Gustafson, D. L.; Emre, E.

In: IEEE Transactions on Aerospace and Electronic Systems, Vol. 26, No. 5, 01.01.1990, p. 876-887.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Extended Solution To Multiple Maneuvering Target Tracking

AU - Chung, Yi-Nung

AU - Gustafson, D. L.

AU - Emre, E.

PY - 1990/1/1

Y1 - 1990/1/1

N2 - An improved algorithm for tracking multiple maneuvering targets is presented. This approach is implemented with an approximate adaptive filter consisting of the 1-step conditional maximumlikelihood technique together with the extended Kalman filter and an adaptive maneuvering compensator. In order to avoid the extra computational burden of considering events with negligible probability, a validation matrix is defined in the tracking structure. Via this approach, both data association and target maneuvering problems can be solved simultaneously Detailed Monte-Carlo simulations of the algorithm for many tracking situations are described. Computer simulation results indicate that this approach successfully tracks multiple maneuvering targets over a wide range of conditions.

AB - An improved algorithm for tracking multiple maneuvering targets is presented. This approach is implemented with an approximate adaptive filter consisting of the 1-step conditional maximumlikelihood technique together with the extended Kalman filter and an adaptive maneuvering compensator. In order to avoid the extra computational burden of considering events with negligible probability, a validation matrix is defined in the tracking structure. Via this approach, both data association and target maneuvering problems can be solved simultaneously Detailed Monte-Carlo simulations of the algorithm for many tracking situations are described. Computer simulation results indicate that this approach successfully tracks multiple maneuvering targets over a wide range of conditions.

UR - http://www.scopus.com/inward/record.url?scp=0025493210&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0025493210&partnerID=8YFLogxK

U2 - 10.1109/7.102720

DO - 10.1109/7.102720

M3 - Article

AN - SCOPUS:0025493210

VL - 26

SP - 876

EP - 887

JO - IEEE Transactions on Aerospace and Electronic Systems

JF - IEEE Transactions on Aerospace and Electronic Systems

SN - 0018-9251

IS - 5

ER -