Multi-dimensional high-precision track intelligent prediction method based on line segment clustering

Abstract

The invention discloses a multi-dimensional high-precision track intelligent prediction method based on line segment clustering. The method includes discretizing the continuous track data; carrying out abrupt change longitude data processing, data cleaning and normalization processing; compressing track data by using a Douglas-Peucker algorithm; using a DBSCAN clustering algorithm for clustering flight paths, selecting flight path clusters corresponding to emergency situations according to different emergency situations under multi-dimensional factors, performing flight path prediction througha flight path prediction neural network model, and finishing a multi-dimensional high-precision flight path prediction task. According to the invention, the original flight path data is compressed, so that the calculation pressure is greatly reduced under the condition of reserving flight path characteristics, the operation time is shortened, and the operation efficiency is improved; a convolution and LSTM neural network model is adopted, convolution is used for feature extraction, and the track prediction precision of the LSTM neural network model can be improved.

Description

Technical field [0001] The invention relates to the technical field of target tracking, in particular to a multi-dimensional high-precision track intelligent prediction method based on line segment clustering. Background technique [0002] For the specific task of mastering the trajectory of a suspicious moving target, on the one hand, it is necessary to learn the law of the suspicious moving target’s trajectory and predict the future trajectory of the moving target with high accuracy. On the other hand, it is necessary to consider multi-dimensional factors under realistic conditions. Such as emergencies, international hot spots, weather conditions, etc., the track information of moving targets can be predicted with high accuracy. [0003] The method of collecting track data of moving targets (such as ships) in the ocean is usually to obtain the data information of the current position of the ship intermittently. According to the different state of the ship, the position is broadca...

AI Technical Summary

Problems solved by technology

[0006] In view of this, the present invention provides a multi-dimensional high-precision track intelligent prediction method based on line segment clustering, which is used for the processing of track data of moving targets at sea and multi-dimensional factors under realistic conditions, providing a simple calculation, A trajectory prediction method for maritime moving targets with flexible constraints and requirements and excellent efficiency, to solve the problem of trajectory prediction under multi-dimensional conditions

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