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Airborne behaviour monitoring using Gaussian processes with map information.pdf (2.97 MB)

Airborne behaviour monitoring using Gaussian processes with map information

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posted on 2015-06-12, 15:13 authored by Hd Oh, Hyo-Sang Shin, Seungkeun Kim, Antonios Tsourdos, Barry A. White
This study proposes an airborne behaviour monitoring methodology of ground vehicles based on a statistical learning approach with domain knowledge given by road map information. To monitor and track the moving ground target using unmanned aerial vehicle aboard a moving target indicator, an interactive multiple model (IMM) filter is firstly applied. The IMM filter consists of an on-road moving mode using a road-constrained filter and an off-road moving mode using a conventional filter. Mode probability is also calculated from the IMM filter, and it provides deviation of the vehicle from the road. Then, a novel hybrid algorithm for anomalous behaviour recognition is developed using a Gaussian process regression on velocity profile along the one-dimensionalised position of the vehicle, as well as the deviation of the vehicle. To verify the feasibility and benefits of the proposed approach, a numerical simulation is performed using realistic car trajectory data in a city traffic.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

IET RADAR SONAR AND NAVIGATION

Volume

7

Issue

4

Pages

393 - 400 (8)

Citation

OH, H. ... et al, 2013. Airborne behaviour monitoring using Gaussian processes with map information. IET Radar, Sonar and Navigation, 7 (4), pp. 393 - 400.

Publisher

© Institution of Engineering and Technology (IET)

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2013

Notes

This paper is a postprint of a paper submitted to and accepted for publication in IET Radar, Sonar and Navigation and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.

ISSN

1751-8784

Language

  • en

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