Inland waterway sparse AIS trajectory estimation method based on navigation experience

HUANG Liang; LIU Yi; WEN Yuan-qiao; GENG  Xiao-qiao; SUN Teng-da

doi:10.16411/j.cnki.issn1006-7736.2017.03.002

Journal of Dalian Maritime University >

2017 , Vol. 43 >Issue 3: 7 - 13

DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2017.03.002

Inland waterway sparse AIS trajectory estimation method based on navigation experience

HUANG Liang ,
LIU Yi ,
WEN Yuan-qiao ,
GENG Xiao-qiao ,
SUN Teng-da

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(1. School of Navigation, Wuhan University of Technology, Wuhan 430063,China; 2. Hubei Key Laboratory of Inland Shipping Technology, Wuhan 430063,China; 3. China Transport Telecommunications & Information Center, Beijing 100011,China)

Received date: 2016-12-13

Revised date: 2017-04-08

Online published: 2017-04-08

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Abstract

In the inland navigation environment, the serious AIS signal congestion and loss result in the ship AIS trajectory to be sparse and discontinuous. Traditional numerical analysis method is used to fit the lost trajectory of ships, and it cannot adapt to the complicated inland waterways with complicated bend, and is prone to cross the land coast. In this paper, a trajectory estimation method for inland river ship was proposed based on navigation experience. Based on the spatial consistency, time consistency and heading consistency, the history similar ship trajectories were extracted for neighbor sampling points of sparse trajectory, and the navigation experience was estimated by the method of Kernel density estimation, and navigational heat distribution map was modelled. And then the optimal route was calculated as approximate estimation trajectory in consideration of ship movement trend based on navigation heat. Three typical inland river channel scenarios were selected to carry out sparse trajectory restoration experiments. Results show that the proposed method can adapt well to the complex terrain of the inland waterway.

Key words： trajectory in inland waterway; automatic identification system(AIS); navigation experience; Kernel density estimation; trajectory restoring

Cite this article

HUANG Liang , LIU Yi , WEN Yuan-qiao , GENG Xiao-qiao , SUN Teng-da . Inland waterway sparse AIS trajectory estimation method based on navigation experience[J]. Journal of Dalian Maritime University, 2017 , 43(3) : 7 -13 . DOI: 10.16411/j.cnki.issn1006-7736.2017.03.002

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