An aircraft intention-based flight behavior identification method in an autonomous operation mode

By constructing an aircraft flight behavior feature system and the BIRCH clustering algorithm, the real-time problem of full-range flight behavior recognition under autonomous operation mode was solved, enabling dynamic updates and accurate trajectory prediction, thereby improving the safety and adaptability of aircraft flight.

CN119807784BActive Publication Date: 2025-11-25NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Patent Information

Application Number
CN202411770195.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-12-04
Publication Date
2025-11-25
Estimated Expiration
2044-12-04

AI Technical Summary

Technical Problem

Existing technologies lack a method for recognizing flight behavior throughout the entire flight in autonomous operation mode, which cannot meet real-time requirements and ignores the impact of the aircraft's time characteristics on behavior, resulting in an inability to adapt to dynamically changing airspace environments.

Method used

An aircraft flight behavior feature system is constructed. The BIRCH clustering algorithm is used to cluster the spatiotemporal features of aircraft. Combined with the aircraft flight intention model, dynamic updates and real-time identification of aircraft flight behavior are achieved.

Benefits of technology

It enables real-time identification and dynamic updating of flight behavior throughout the entire flight, adapts to dynamic airspace environments, and improves the accuracy of trajectory prediction and flight safety.

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Abstract

The application discloses a flight behavior recognition method based on aircraft intention in an autonomous operation mode. Firstly, aircraft behavior features are extracted from the time and space levels; secondly, an aircraft flight intention model in a typical flight scene is constructed; thirdly, the aircraft behavior features are analyzed by clustering based on a BIRCH clustering model, and the typical behaviors of the aircraft in flight are divided; and finally, the real-time behavior feature values are calculated based on the flight intention model, and online behavior recognition of the aircraft flight is realized. The aircraft behavior features are constructed from the time and space angles, so that the aircraft behavior is more visualized. In addition, the aircraft flight intention model can adapt to dynamic change scenes and is more flexible. Finally, the BIRCH model can adapt to the process of incremental clustering and meet the real-time performance of online behavior recognition.
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