• Performance evaluation of nonl...

Result: Performance evaluation of nonlinear filters for tracking multiple ballistic targets

Title:
Performance evaluation of nonlinear filters for tracking multiple ballistic targets
Authors:
SINHA, A, NANDAKUMARAN, N, SUTHARSAN, S, KIRUBARAJAN, T, EL-FALLAH, A, ZATEZALO, A
Source:
Signal processing, sensor fusion, and target recognition XIV (28-30 March 2005, Orlando, Florida, USA)Proceedings of SPIE, the International Society for Optical Engineering. :220-231
Publisher Information:
Bellingham WA: SPIE, 2005.
Publication Year:
2005
Physical Description:
print, 14 ref 1
Original Material:
INIST-CNRS
Subject Terms:
Electronics, Electronique, Optics, Optique, Physics, Physique, Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Signal, bruit, Signal, noise, Détection, estimation, filtrage, égalisation, prédiction, Detection, estimation, filtering, equalization, prediction, Algorithme, Algorithm, Algoritmo, Balistique, Ballistics, Balística, Bruit non gaussien, Non gaussian noise, Ruido no gaussiano, Cible multiple, Multiple target, Blanco múltiple, Densité probabilité, Probability density, Densidad probabilidad, Evaluation performance, Performance evaluation, Evaluación prestación, Filtre non linéaire, Non linear filter, Filtro no lineal, Filtre particule, Particle filter, Filtro partículas, Filtre poursuite, Tracking filters, Implémentation, Implementation, Implementación, Modèle non linéaire, Non linear model, Modelo no lineal, Moment statistique, Statistical moment, Momento estadístico, Ordre 1, First order, Orden 1, Performance algorithme, Algorithm performance, Resultado algoritmo, Poursuite cible, Target tracking, Simulation, Simulación, Système non linéaire, Non linear system, Sistema no lineal, Trace particule, Particle tracks, Traza particula
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Electrical and Computer Engineering Department, McMaster University 1280 Main Street, Hamilton, Ontario L8S 4K1, Canada
Scientific systems Company, Inc. 500 West Cummings Park, Suite 3000, Woburn, MA 01801 - 6580, United States
ISSN:
0277-786X
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=17809850
Rights:
Copyright 2006 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Telecommunications and information theory
Accession Number:
edscal.17809850
Database:
PASCAL Archive

Further Information

The particle filter is an effective technique for target tracking in the presence of nonlinear system model, nonlinear measurement model or non-Gaussian noise in the system and/or measurement processes. In this paper, we compare three particle filtering algorithms on a spawning ballistic target tracking scenario. One of the algorithms, the tagged particle filter (TPF), was recently developed by us. It uses separate sets of particles for separate tracks. However, data association to different tracks is interdependent. The other two algorithms implemented in this paper are the probability hypothesis density (PHD) algorithm and the joint multitarget probability density (JMPD). The PHD filter propagates the first order statistical moment of multitarget density using particles. While, the JMPD stacks the states of a number of targets to form a single particle that is representative of the whole system. Simulation results are presented to compare the performances of these algorithms.