Home // ADAPTIVE 2010, The Second International Conference on Adaptive and Self-Adaptive Systems and Applications // View article
Authors:
Lokukaluge Perera
Carlos Guedes Soares
Keywords: Laser Measurement System, Competitive Neural Networks, Target tracking, Data Points Tracking
Abstract:
To improve safety and security issues, maneuvering target detection and tracking are important facilities for navigation systems. Therefore, conventional navigation systems are equipped with Radar-based systems for the same purpose. However, Radar systems suffer some practical problems that are associated with the targets in close quarter navigation. Furthermore, Radar singles attenuate with distance, weather (ie. rain) and sea conditions, where the target tacking performances are degraded. Therefore, a Laser Measurement System (LMS) is proposed in this study to overcome the problems faced by the conventional Radar systems at close quarter navigation as well as bad weather and environmental conditions. Furthermore, capabilities of a LMS to measure accurate distance in close proximity as well as to observe the shape and size of the target are illustrated. In this study, each target is approximated by a cluster of data points rather than a single point target that is the main contribution in this paper. The adaptive Neural Network approach is proposed as a method of tracking maneuvering targets that are represented by clusters of data points. Successful simulation and experimental results of target detection and tracking that are tested on a experimental platform, SICK© LMS, are also presented in this paper.
Pages: 84 to 90
Copyright: Copyright (c) IARIA, 2010
Publication date: November 21, 2010
Published in: conference
ISSN: 2308-4146
ISBN: 978-1-61208-109-0
Location: Lisbon, Portugal
Dates: from November 21, 2010 to November 26, 2010