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Authors: Cheryl Eisler 1 ; Peter Dobias 1 and Kenzie MacNeil 2

Affiliations: 1 Defence Research and Development Canada, Canada ; 2 CAE Inc., Canada

ISBN: 978-989-758-218-9

ISSN: 2184-4372

Keyword(s): Satellite Automatic Identification System (S-AIS), Surveillance, Probability of Detection, Parametric, Performance, Model, Signal Collision.

Related Ontology Subjects/Areas/Topics: Agents ; Applications ; Artificial Intelligence ; Bioinformatics ; Biomedical Engineering ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Methodologies and Technologies ; Operational Research ; Pattern Recognition ; Simulation ; Software Engineering

Abstract: The question of having sufficient surveillance capability to detect illicit behaviour in order to inform decision makers in a timely fashion is of the ultimate importance to defence, security, law enforcement, and regulatory agencies. Quantifying such capability provides a means of informing asset allocation, as well as establishing the link to risk of mission failure. Individual sensor models can be built and integrated into a larger model that layers sensor performance using a set of metrics that can take into account area coverage, coverage times, revisit rates, detection probabilities, and error rates. This paper describes an implementation of a parametric model for Satellite Automated Identification System (S-AIS) sensor performance. Utilizing data from a real data feed, the model was able to determine the percentage of uncorrupted S-AIS messages and the probability of detection of at least one correct S-AIS message received during an observation interval. It is importan t to note that the model implementation was not actively calculating the effect of message overlap based on satellite altitude and footprint width, or reductions in collisions due to signal decollision algorithms. (More)

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Paper citation in several formats:
Eisler, C.; Dobias, P. and MacNeil, K. (2017). A Surveillance Application of Satellite AIS - Utilizing a Parametric Model for Probability of Detection.In Proceedings of the 6th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-218-9, ISSN 2184-4372, pages 211-218. DOI: 10.5220/0006108302110218

@conference{icores17,
author={Cheryl Eisler. and Peter Dobias. and Kenzie MacNeil.},
title={A Surveillance Application of Satellite AIS - Utilizing a Parametric Model for Probability of Detection},
booktitle={Proceedings of the 6th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2017},
pages={211-218},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006108302110218},
isbn={978-989-758-218-9},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - A Surveillance Application of Satellite AIS - Utilizing a Parametric Model for Probability of Detection
SN - 978-989-758-218-9
AU - Eisler, C.
AU - Dobias, P.
AU - MacNeil, K.
PY - 2017
SP - 211
EP - 218
DO - 10.5220/0006108302110218

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