Journal of System Simulation
Abstract
Abstract: Current trajectory simulation methods inadequately address geometric shape features and kinematic properties of the target trajectory. To bridge this gap, a target trajectory shape simulation algorithm based on kinematic laws was proposed. The polar coordinate equations and curvature equations of multiple trajectories were integrated. The aircraft state parameters were solved by combining kinematic equations. Angular Gaussian noise was introduced to enhance trajectory diversity and authenticity. Additionally, a multi-perspective trajectory shape recognition algorithm was designed, which could effectively integrate image and sequential multi-modal features by adopting a multilayer perceptron, enabling precise trajectory shape recognition. Experimental results demonstrate that the proposed algorithm can generate diverse trajectory data conforming to physical laws. The multiperspective recognition models achieve higher accuracy compared to single-perspective recognition models, validating the effectiveness of both trajectory shape simulation and recognition algorithms.
Recommended Citation
Feng, Xuejian; Ding, Han; Tong, Yiqi; Huo, Chaoying; and Zhang, Yanjin
(2026)
"Simulation and Multi-perspective Recognition Algorithm for Typical Trajectory Shapes,"
Journal of System Simulation: Vol. 38:
Iss.
3, Article 13.
DOI: 10.16182/j.issn1004731x.joss.25-0022
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol38/iss3/13
First Page
725
Last Page
735
CLC
TP391.9
Recommended Citation
Feng Xuejian, Ding Han, Tong Yiqi, et al. Simulation and Multi-perspective Recognition Algorithm for Typical Trajectory Shapes[J]. Journal of System Simulation, 2026, 38(3): 725-735.
DOI
10.16182/j.issn1004731x.joss.25-0022
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