000	02017cam  2200229za 4500
001	9.830211
003	CaOODSP
005	20221107145459
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008	170113s2014    nsca   |o    f|0| 0 eng d
040	|aCaOODSP|beng
043	|an-cn---
086	1 |aD69-36/2014E-PDF
100	1 |aHammond, T.R.
245	10|aApplications of probabilistic interpolation to ship tracking |h[electronic resource] / |cT.R. Hammond.
260	|a[Darmouth, Nova Scotia] : |bDefence Research and Development Canada Atlantic Research Centre, |c[2014]
300	|a1 vol. (unnumbered) : |bcol. ill.
504	|aIncludes bibliographic references.
520	3 |a"Ships report their own position at predictable intervals via the Automatic Identification System (AIS) and Long Range Identification and Tracking (LRIT). Those able to receive these position reports can track the movement of vessels, but using self-reported positions raises new estimation challenges. One of these is the interpolation problem, which considers what happened between two successive position reports, A and B, from the same ship. This paper illustrates the practical significance of this problem in issues from oil-spill investigation to maritime security and fisheries management. It outlines ageneral Bayesian approach to the problem that is based on simulating large numbers of random tracks. The approach is illustrated using a fictitious Arctic scenario in which a contact, obtained from a radar satellite system, is to be associated with one of three AIS tracks, in the presence of ice. The method shows how the ice-breaking capabilities of the vessels can be accounted for in the association problem, a challenging task for traditional methods. Finally, the paper shows how to generalize from this simple association problem to more complex cases"--Abstract.
692	07|2gccst|aShips
710	1 |aCanada. |bDefence R&D Canada.
856	40|qPDF|s6.19 MB|uhttps://publications.gc.ca/collections/collection_2017/rddc-drdc/D69-36-2014-eng.pdf