Adaptive typical trajectory generation based on geometric algebra

Journal of Civil Aviation University of China ›› 2025, Vol. 43 ›› Issue (6): 38-45.

• Air Transportation Management • Previous Articles Next Articles

Adaptive typical trajectory generation based on geometric algebra

1. Intelligent Signal and Image Processing Key Lab of Tianjin, CAUC, Tianjin 300300, China; 2. The Automotive Electronics

Department of Jingwei Hirain (Tianjin) Research & Development Co., Ltd., Tianjin 300300, China

Received:2024-02-20 Revised:2024-06-20 Online:2025-12-20 Published:2026-01-10

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Abstract

Abstract:

By analyzing the performance of density-based spatial clustering of applications with noise (DBSCAN) and fuzzy

C-means (FCM) clustering, a fast adaptive typical trajectory generation method based on geometric algebra is

proposed. Firstly, the K-means clustering algorithm is used to normalize the flight operation time. Then, lever aging the superior capabilities of geometric algebra in spatiotemporal representation and computation, geometric

algebraic descriptions are formulated for trajectory turn determination, DBSCAN clustering and FCM clustering.

Finally, in the geometric algebraic space, DBSCAN clustering and FCM clustering are carried out adaptively to

form typical trajectories of turn motion state and straight motion state respectively. Experimental results show

that the adaptive typical trajectories achieve over 30% faster generation speed compared to conventional Euclidean space methods.

Key words:

geometric algebra, density-based spatial clustering of applications with noise (DBSCAN) clustering, fuzzy

C-means (FCM) clustering, typical trajectory

CLC Number:

V328.3

JIAO Weidong , LI Chunyang, , WU Haobo , LI Taiyu.

Adaptive typical trajectory generation based on geometric algebra

[J]. Journal of Civil Aviation University of China, 2025, 43(6): 38-45.

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Adaptive typical trajectory generation based on geometric algebra

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