Accession Number:

AD1113111

Title:

Bayesian Track-to-Graph Association for Maritime Traffic Monitoring

Corporate Author:

CENTRE FOR MARITIME RESEARCH AND EXPERIMENTATION LA SPEZIA (ITALY) LA SPEZIA

Report Date:

2019-05-01

Abstract:

We present a hypothesis test to associate ship track measurements to an edge of a given graph that statistically models common traffic routes in a given area of interest. The association algorithm is based on the hypothesis that ship velocities are modeled by mean-reverting stochastic processes. Prior knowledge about the traffic is provided by the graph in form of probability density functions of the mean-reverting kinematic parameters for each node and edge of the graph, which are exploited in the formalization of the association algorithm. Tests on real Automatic Identification System AIS data show a qualitatively good association performance. Future developments of this work include the development of specific quantitative metrics to assess the association performance.

Descriptive Note:

Conference Paper

Supplementary Note:

2018 26th European Signal Processing Conference (EUSIPCO) , 03 Sep 2018, 07 Sep 2018, DTIC Crawl

Pages:

0008

Communities Of Interest:

Modernization Areas:

Distribution Statement:

Approved For Public Release;

File Size:

1.92MB