Ship propagation as a harmonically bound particle – Using the Kramers equation for vessel traffic data

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Authors
  1. Maybury, D.W.
Corporate Authors
Defence Research and Development Canada, Centre for Operational Research and Analysis, Ottawa ON (CAN)
Abstract
Understanding the statistical patterns of ship propagation along well-defined lanes increases domain awarness by giving security experts a clearer picture of the background in which targets of interest appear. I present a model which describes ship propagation in non-maneuvering modes, based on Kalman filtering with Brownian motion in the presence of a restoring potential. As a proof-of-principle demonstration of the algorithm, I use Automatic Identification System (AIS) data from a survey ship in the western Arctic Ocean. I find evidence for a non-vanishing potential along imputed non-maneuvering modes of operation. Imputed lanes from the AIS traffic data contain a potential degeneracy between drift and diffusion in the model calibration, which I break by fiat. Testing the model with ship traffic data along known shipping lanes will remove this ambiguity. The result in this paper, using the available data, successfully demonstrates the empirical model estimation technique, making the method available for further ship traffic analysis.

Il y a un résumé en français ici.

Keywords
Object Tracking;Data Fusion;Filtering
Report Number
DRDC-RDDC-2017-R045 — Scientific Report
Date of publication
01 Nov 2017
Number of Pages
26
DSTKIM No
CA045466
CANDIS No
805876
Format(s):
Electronic Document(PDF)

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