Authors: J. Dezert, A. Tchamova, L. Bojilov, P. Konstantinova
The main objective of this paper is to investigate the impact of the quality of attribute data source on the performance of a target tracking algorithm. An array of dense scenarios arranged according to the distance between closely spaced targets is studied by different confusion matrices. The used algorithm is Generalized Data Association (GDA-MTT) algorithm for multiple target tracking processing kinematic as well as attribute data. The fusion rule for attribute data is based on Dezert-Smarandache Theory (DSmT). Besides the main goal a comparison is made between the cited above algorithm and an algorithm with Kinematic based only Data Association (KDAMTT). The measures of performance are evaluated using intensive Monte Carlo simulation.
Comments: 5 Pages.
Download: PDF
[v1] 2017-06-13 00:53:04
Unique-IP document downloads: 65 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.