Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Anomaly Detection Method of Ship Trajectory Based on Channel Model

An anomaly detection and ship trajectory technology, applied in character and pattern recognition, instrumentation, calculation, 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, and increase the detection The effect of precision

Active Publication Date: 2021-07-27
NAVAL UNIV OF ENG PLA
View PDF4 Cites 0 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 areas, the communication mechanism is not smooth, and real-time and continuous AIS data cannot be obtained, most algorithms are difficult. To achieve a satisfactory application effect

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
  • Anomaly Detection Method of Ship Trajectory Based on Channel Model
  • Anomaly Detection Method of Ship Trajectory Based on Channel Model
  • Anomaly Detection Method of Ship Trajectory Based on 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 abnormality detection method based on a channel model, comprising the following steps: 1. Acquiring historical AIS data in a selected time interval; Step 2. Preprocessing the historical AIS data; 3. The waypoints and routes of the waterway model are respectively extracted from the AIS data, and the waypoints and routes are respectively regarded as the vertices and edges of the graph in graph theory to form the waterway model: Step 4. Weight the waterway model according to the time element, and get The final channel model; step 5, comparing the final channel model with the track to be detected, and judging whether the track is abnormal according to whether the track to be detected appears in the final channel model. By combining the advantages of the point-based algorithm and the trajectory-based algorithm, the invention fully excavates the historical rules of navigation in the hotspot area, and obtains the behavior patterns and spatio-temporal information left by the navigation trajectory; it can perform short-term abnormal monitoring and long-term monitoring Abnormal monitoring.

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
Patent Type & Authority Patents(China)
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 Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products