Identification of Non-Broadcasting Vessels – Basic Description for Non-Cooperatively Identifying Vessels with Combinatorial Statistics

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Authors
  1. Schaub, D.E.
Corporate Authors
Defence Research and Development Canada, Atlantic Research Centre, Halifax NS (CAN)
Abstract
Identification of targets has historically been conducted on an ad-hoc basis. Over the past two decades, the development of the recognized maritime picture—particularly in operations centres—has become heavily reliant on the continual intake of automatic identification system (AIS) messages. Arguably, situational awareness has improved considerably owing to the enormous increase in self-reports of vessels that would otherwise remain undetected or unidentified. While providing ready access to seemingly high-quality target identity information, AIS remains highly vulnerable to inadvertent or malicious disruption. Moreover, vessels posing threats are either unlikely to broadcast AIS messages at all or transmit false identification or location information. Under these circumstances, it becomes imperative to develop robust methods of identifying vessels using information besides self-reported identity. To this end, the present work qualitatively describes a combinatorial framework for non-cooperative identification, with the objective of motivating the development of a flexible system (both tactical and operational) that may be used to identify non-reporting (dark) vessels and confirm the stated identity of self-reporting vessels.

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Keywords
bayesian;identification;combinatorial;combinatorics;AIS;MCMC;markov;chain monte carlo;permanent
Report Number
DRDC-RDDC-2015-R286 — Scientific Report
Date of publication
01 Dec 2015
Number of Pages
28
DSTKIM No
CA042777
CANDIS No
804146
Format(s):
Electronic Document(PDF)

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