Parallel particle filters for multiple target tracking
Joint Authors
Abd al-Nur, Sebbagh
Hisham, Tebbikh
Source
The International Arab Journal of Information Technology
Issue
Vol. 13, Issue 6 (31 Dec. 2016)8 p.
Publisher
Publication Date
2016-12-31
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Topics
Abstract EN
The Multiple Targets Tracking (MTT) problem is addressed in signal and image processing.
When the state and measurement models are linear, we can find several algorithms that yield good performances in MTT problem, among them, the Multiple Hypotheses Tracker (MHT) and the Joint Probabilistic Data Association Filter (JPDAF).
However, if the state and measurement models are nonlinear, these algorithms break down.
In this paper we propose a method based on particle filters bank, where the objective is to make a contribution for estimating the trajectories of several targets using only bearings measurements.
The main idea of this algorithm is to combine the Multiple Model approach (MM) with Sequential Monte Carlo methods (SMC).
The result from this combination is a Nonlinear Multiple Model Particle Filters algorithm (NMMPF) able to estimate the trajectories of multiple targets.
American Psychological Association (APA)
Abd al-Nur, Sebbagh& Hisham, Tebbikh. 2016. Parallel particle filters for multiple target tracking. The International Arab Journal of Information Technology،Vol. 13, no. 6.
https://search.emarefa.net/detail/BIM-654813
Modern Language Association (MLA)
Abd al-Nur, Sebbagh& Hisham, Tebbikh. Parallel particle filters for multiple target tracking. The International Arab Journal of Information Technology Vol. 13, no. 6 (Dec. 2016).
https://search.emarefa.net/detail/BIM-654813
American Medical Association (AMA)
Abd al-Nur, Sebbagh& Hisham, Tebbikh. Parallel particle filters for multiple target tracking. The International Arab Journal of Information Technology. 2016. Vol. 13, no. 6.
https://search.emarefa.net/detail/BIM-654813
Data Type
Journal Articles
Language
English
Notes
Includes appendix.
Record ID
BIM-654813