Tracking algorithm compensating acceleration for 3D maneuvering target with PSO-FCM

Hyun Seung Son, Jin Bae Park, Young Hoon Joo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper presents an intelligent tracking method for nonlinear maneuvering target by compartmentalizing external noises of 3D maneuvering target. Proposed method makes the filter recognize the maneuvering target as linear one by separating acceleration properly from the overhaul noises. For achieving that, we use the particle swam optimization-fuzzy c-means (PSO-FCM) clustering as the criteria of methodology. The positional difference between measured point and predicted one is separated into acceleration and noise. Compartmentalized external noises plays the role of acceleration in accordance with assigned position and its quantity. Proposed algorithm makes approximated acceleration to be compensated and approximated noise is filtered by Kalman filter (KF). To depict the real maneuvering target and track the target with unlimited condition, we handle 3D dynamic model. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012
DOIs
Publication statusPublished - 2012 Oct 23
Event2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012 - Brisbane, QLD, Australia
Duration: 2012 Jun 102012 Jun 15

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Other

Other2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012
CountryAustralia
CityBrisbane, QLD
Period12/6/1012/6/15

Fingerprint

Fuzzy C-means
Target
Optimization
Fuzzy C-means Clustering
Kalman filters
Dynamic models
3D Model
Kalman Filter
Dynamic Model
Filter
Methodology

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Software
  • Artificial Intelligence
  • Applied Mathematics

Cite this

Son, H. S., Park, J. B., & Joo, Y. H. (2012). Tracking algorithm compensating acceleration for 3D maneuvering target with PSO-FCM. In 2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012 [6250839] (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZ-IEEE.2012.6250839
Son, Hyun Seung ; Park, Jin Bae ; Joo, Young Hoon. / Tracking algorithm compensating acceleration for 3D maneuvering target with PSO-FCM. 2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012. 2012. (IEEE International Conference on Fuzzy Systems).
@inproceedings{3577b4044108409d921878cd55e6a179,
title = "Tracking algorithm compensating acceleration for 3D maneuvering target with PSO-FCM",
abstract = "This paper presents an intelligent tracking method for nonlinear maneuvering target by compartmentalizing external noises of 3D maneuvering target. Proposed method makes the filter recognize the maneuvering target as linear one by separating acceleration properly from the overhaul noises. For achieving that, we use the particle swam optimization-fuzzy c-means (PSO-FCM) clustering as the criteria of methodology. The positional difference between measured point and predicted one is separated into acceleration and noise. Compartmentalized external noises plays the role of acceleration in accordance with assigned position and its quantity. Proposed algorithm makes approximated acceleration to be compensated and approximated noise is filtered by Kalman filter (KF). To depict the real maneuvering target and track the target with unlimited condition, we handle 3D dynamic model. Finally, some examples are provided to show the effectiveness of the proposed algorithm.",
author = "Son, {Hyun Seung} and Park, {Jin Bae} and Joo, {Young Hoon}",
year = "2012",
month = "10",
day = "23",
doi = "10.1109/FUZZ-IEEE.2012.6250839",
language = "English",
isbn = "9781467315067",
series = "IEEE International Conference on Fuzzy Systems",
booktitle = "2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012",

}

Son, HS, Park, JB & Joo, YH 2012, Tracking algorithm compensating acceleration for 3D maneuvering target with PSO-FCM. in 2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012., 6250839, IEEE International Conference on Fuzzy Systems, 2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012, Brisbane, QLD, Australia, 12/6/10. https://doi.org/10.1109/FUZZ-IEEE.2012.6250839

Tracking algorithm compensating acceleration for 3D maneuvering target with PSO-FCM. / Son, Hyun Seung; Park, Jin Bae; Joo, Young Hoon.

2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012. 2012. 6250839 (IEEE International Conference on Fuzzy Systems).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Tracking algorithm compensating acceleration for 3D maneuvering target with PSO-FCM

AU - Son, Hyun Seung

AU - Park, Jin Bae

AU - Joo, Young Hoon

PY - 2012/10/23

Y1 - 2012/10/23

N2 - This paper presents an intelligent tracking method for nonlinear maneuvering target by compartmentalizing external noises of 3D maneuvering target. Proposed method makes the filter recognize the maneuvering target as linear one by separating acceleration properly from the overhaul noises. For achieving that, we use the particle swam optimization-fuzzy c-means (PSO-FCM) clustering as the criteria of methodology. The positional difference between measured point and predicted one is separated into acceleration and noise. Compartmentalized external noises plays the role of acceleration in accordance with assigned position and its quantity. Proposed algorithm makes approximated acceleration to be compensated and approximated noise is filtered by Kalman filter (KF). To depict the real maneuvering target and track the target with unlimited condition, we handle 3D dynamic model. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

AB - This paper presents an intelligent tracking method for nonlinear maneuvering target by compartmentalizing external noises of 3D maneuvering target. Proposed method makes the filter recognize the maneuvering target as linear one by separating acceleration properly from the overhaul noises. For achieving that, we use the particle swam optimization-fuzzy c-means (PSO-FCM) clustering as the criteria of methodology. The positional difference between measured point and predicted one is separated into acceleration and noise. Compartmentalized external noises plays the role of acceleration in accordance with assigned position and its quantity. Proposed algorithm makes approximated acceleration to be compensated and approximated noise is filtered by Kalman filter (KF). To depict the real maneuvering target and track the target with unlimited condition, we handle 3D dynamic model. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

UR - http://www.scopus.com/inward/record.url?scp=84867591834&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84867591834&partnerID=8YFLogxK

U2 - 10.1109/FUZZ-IEEE.2012.6250839

DO - 10.1109/FUZZ-IEEE.2012.6250839

M3 - Conference contribution

SN - 9781467315067

T3 - IEEE International Conference on Fuzzy Systems

BT - 2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012

ER -

Son HS, Park JB, Joo YH. Tracking algorithm compensating acceleration for 3D maneuvering target with PSO-FCM. In 2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012. 2012. 6250839. (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZ-IEEE.2012.6250839