Ship track abnormity detection method based on navigation channel model

An anomaly detection and ship trajectory technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems that the algorithm is difficult to achieve the application effect, the communication mechanism is not smooth, etc., to improve the usability, improve the preprocessing speed, The effect of improving efficiency

Active Publication Date: 2019-09-06
NAVAL UNIV OF ENG PLA
View PDF4 Cites 22 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] Generally speaking, it is easy to implement anomaly monitoring for ships with complete trajectories, but due to the changeable marine environment, especially in remote sea ar

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Ship track abnormity detection method based on navigation channel model
  • Ship track abnormity detection method based on navigation channel model
  • Ship track abnormity detection method based on navigation channel model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0029] A ship track abnormality detection method based on the channel model designed by the present invention, such as figure 1 As shown, it includes the following steps:

[0030] Step 1: Obtain the historical AIS data within the selected time interval from the shipping service provider. The abnormal detection of the ship trajectory is essentially judged according to the behavior pattern of the ship, and historical records are needed as a standard for comparison;

[0031] Step 2: Perform preprocessing on the historical AIS data to delete redundant data, delete noise data, segment uncertain trajectories, sample and interpolate the trajectory, and obtain AIS data that does not contain redundancy and noise, and improves the accuracy of the algorithm, so as to improve The accuracy of abnormal monitoring results is affected by the ship’s navigation ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a ship track abnormity detection method based on a navigation channel model. The ship track abnormity detection method comprises the following steps: 1, obtaining historical AIS data in a selected time interval; 2, preprocessing the historical AIS data; 3, respectively extracting waypoints and air routes of the channel model from the preprocessed AIS data, and respectivelytaking the waypoints and the air routes as vertexes and edges of a graph in a graph theory to form the channel model: step 4, weighting the channel model according to time factors to obtain a final channel model; and 5, comparing the final channel model with the to-be-detected track, and judging whether the track is abnormal according to whether the to-be-detected track appears in the final channel model. According to the method, the advantages of a point-based algorithm and a track-based algorithm are fused, the historical law of navigation in a hot spot area is fully mined, and the behaviormode and space-time information left by a navigation track are obtained; short-term abnormity monitoring can be carried out, and long-term abnormity monitoring can also be carried out.

Description

technical field [0001] The invention relates to the technical field of ship data processing, in particular to a ship track abnormality detection method based on a channel model. Background technique [0002] In the context of the era of world economic globalization, trade among countries and regions has increased, and the maritime transportation industry has achieved prosperity and development. At the same time, the hidden dangers of maritime navigation safety have gradually become prominent. On the one hand, the current number of ships in the world is huge and increasing day by day, the variety of ships and the complex routes make it difficult to predict the movement behavior of ships, and there are unstable factors in the safety environment; on the other hand, due to the limited capacity of terminals and waterways, waterway traffic Congestion, overburdened routes, and the contradiction between the increasing number of ships have emerged, and the criss-crossing channels and...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/00G06K9/40
CPCG06V20/182G06V10/30
Inventor 马良荔牛敬华王永生魏健王亮
Owner NAVAL UNIV OF ENG PLA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products