A method and device for online detection of flight deviation from normal track behavior

Abstract

The invention relates to a flight normal track deviation behavior online detection method and a flight normal track deviation behavior online detection device, which belong to the technical field of aerospace. The flight normal track deviation behavior online detection device comprises an information acquisition module, an air route and track preprocessing module, a space-time matching module, a track matching module and an abnormal track behavior detection module. The flight normal track deviation behavior online detection method comprises the steps of when the deviation between a planned airroute of a flight and a real-time flight path is relatively large, detecting the flight as a target flight, intercepting an air route section of the target flight according to set space-time dimensions; searching for a flight matched in the space-time dimensions from planned air routes of other flights; further calculating the actual flight path distance between the matched flight and the targetflight; and when the target flight is successfully matched with one or more matched flights on the flight path, considering that a similar and reasonable fly-around strategy is adopted, and not givingan abnormal alarm; otherwise, judging that the target flight has flight abnormality and giving an alarm. According to the flight normal track deviation behavior online detection method and the flightnormal track deviation behavior online detection device, online detection of the behavior that the flight deviates from the normal flight track is realized, and the airspace operation safety and flight efficiency are improved.

Description

technical field [0001] The invention belongs to the field of aerospace technology and relates to a method for detecting abnormal track behavior, in particular to an online detection method and device for flight deviation from normal track behavior. Background technique [0002] In the scenario where the airspace structure is complex and the flight situation is unknown, it is the research focus of air traffic management to realize the timely detection and alarm of abnormal track behavior. On the one hand, flights are often prone to deviate from the planned route due to various factors, such as bad weather, air traffic control, and personal behavior of the pilot. Once an accident occurs due to abnormal flight behavior, it is very likely to cause catastrophic On the other hand, since flights often have bypass strategies in the actual operation process, if the difference between the actual track and the planned route is blindly compared, many flights that adopt the bypass strate...

AI Technical Summary

Problems solved by technology

[0003] Among the existing detection methods for flight deviation from the normal track, it is generally difficult to balance detection accuracy and timeliness

In the literature [1], the abnormal flight behavior is detected according to the multi-dimensional characteristics of the track, but this method is an offline detection method, which cannot meet the real-time requirements of air traffic

Literature [2] proposed a method based on airborne flight record data and using DBSCAN cluster analysis to identify abnormal flights. The data scale is small, but flights with the same circumvention strategy are judged to have abnormal flight behavior, which increases the detection "false alarm" rate to a certain extent

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