On Validating Self-Reported Vessel Location – Application of Statistical Methods to Assessing Automatic Identification System Reports


  1. Schaub, D.E.
Corporate Authors
Defence R&D Canada - Atlantic, Dartmouth NS (CAN)
Self-reported information in maritime settings has become increasingly important in issues surrounding navigation, vessel traffic services, and security. While self-reported data may significantly improve the apparent spatial-temporal resolution of vessel positions used to construct the recognized maritime picture, its accuracy is readily compromised by deliberate acts of deception. The present work sought to develop a method of validating automatic identification system positional reports with trusted radar satellite data. The approach presented uses Kalman smoothing to retrospectively interpolate a vessel’s path between radar satellite observations, allowing its location to be estimated for an arbitrary moment in time. A given self-report may then be assessed against a contemporaneous radar satellite estimate using a variety of statistical techniques. Evaluations based on probability ratio analysis, classical hypothesis testing, and nested confidence region analysis were considered. Finally, the method’s range of applicability was studied by examining the interaction between a vessel’s maneuverability and frequency of radar observations. These considerations may be of use in planning future satellite infrastructure.

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Report Number
DRDC-ATLANTIC-TM-2011-320 — Technical Memorandum
Date of publication
01 Jan 2012
Number of Pages
Electronic Document(PDF)

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