Helicopter Flight Action Recognition Based on the Rocket Algorithm
Helicopters have received more and more attention in recent years due to their unique flight characteristics and wide range of applications. Accurate identification of the helicopter’s flight actions is essential for the successful completion of the helicopter flight mission. Due to the complexity of the traditional helicopter flight action recognition method, the accuracy of human recognition is low. In this paper, the Rocket algorithm is used to identify helicopter flight actions. Firstly, the preprocessing of the flight parameter data includes the conversion of category labels and data normalization. Then, the Rocket machine learning model is used to apply the RidgeClassifierCV classifier to identify the helicopter flight action. In this paper, the flight parameter data of real helicopters is used for experiments, and the results show that the accuracy rate is $77.09 \%$, which is significantly higher than that of other machine learning methods.
Authors
- Jie Yang (ORCID: https://orcid.org/0000-0002-4148-0042)
- Yishuo Liu
- Rubing Shen (ORCID: https://orcid.org/0000-0002-5536-1351)
- Taiyu Chen (ORCID: https://orcid.org/0000-0003-4729-7465)
- Guotao Wang (ORCID: https://orcid.org/0000-0002-2487-9609)
- Shoulai Song
Institutions
- Heilongjiang University (CN)
Publication Details
- Published
- 2025-07-25
- DOI
- https://doi.org/10.1109/jcice66205.2025.11182073
- Primary Topic
- Advanced Sensor and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00