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Target abnormal behavior detection method based multidimensional characteristics

A technology of multi-dimensional features and detection methods, used in instruments, character and pattern recognition, computer parts and other directions, and can solve problems such as underutilization of target type, position, speed and heading, abnormal target track position, etc.

Active Publication Date: 2016-10-12
NAVAL AVIATION UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Some scholars have conducted research on track anomaly detection, but the existing methods mainly detect the abnormal position of the target track, and do not make full use of the multi-dimensional features such as the attribute, type, position, speed and heading of the target. When mining the abnormal behavior of the target has limitations

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  • Target abnormal behavior detection method based multidimensional characteristics
  • Target abnormal behavior detection method based multidimensional characteristics
  • Target abnormal behavior detection method based multidimensional characteristics

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Embodiment Construction

[0036] Take the flight track data set of part civil airliner that an Automatic Dependent Surveillance-Broadcast System (ADS-B) receives below as an example, elaborate the present invention according to accompanying drawing, make technical route and operation steps of the present invention clearer.

[0037] The ADS-B data set includes 237 civil aviation flight tracks received in May 2015, and each track includes several multi-dimensional data points. We can directly read the location characteristics, speed characteristics and heading characteristics composed of the latitude, longitude and altitude of the target. The target attribute is friendly and the type is civil aircraft. In order to calculate the multi-factor directional Hausdorff distance between target tracks, we transform the location features of the target track data points from the latitude, longitude and altitude coordinates in the geographic coordinates to the local Cartesian coordinate system. During conversion, th...

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Abstract

The invention discloses a target abnormal behavior detection method based multidimensional characteristics. The method makes the most of attribute, type, position, speed and course features of a target, achieves the mining of an abnormal behavior of the target through the abnormality detection of multidimensional track data, and specifically comprises the steps: 1, inputting a multidimensional track data set of the target, and setting the attribute and type labels of the target; 2, calculating a multifactor directional Hausdorff distance between tracks of the target; 3, determining a neighbor track of each track; 4, calculating the neighbor density of each track; 5, calculating a multidimensional local abnormal factor of each track; 6, carrying out the abnormal detection judgment of each track; 7, setting a target abnormal behavior label. The method is simple in parameter setting, is high in accuracy, is easy for engineering realization, and good in prospect in the fields of pattern recognition and intelligent information processing.

Description

technical field [0001] The invention relates to anomaly detection technology in data mining and high-level fusion technology in information fusion, and belongs to the field of pattern recognition and intelligent information processing. Background technique [0002] Target track data is a multidimensional sequence composed of multidimensional data points. According to the application scenario, the track data can be divided into early warning and monitoring track data, traffic control track data and video monitoring track data, etc.; according to the type of target, track data can be divided into aircraft track data, ship track data, etc. data, vehicle track data, pedestrian track data, animal track data, and tornado track data. In different application scenarios, the multi-dimensional characteristics of the target track data are also different. For example, in the automatic dependent surveillance-broadcast system, the track data usually includes multi-dimensional features su...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/251G06F18/256
Inventor 潘新龙王海鹏何友熊伟周伟彭煊夏沭涛刘瑜
Owner NAVAL AVIATION UNIV