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| Mercator-Projection-Based Online Trajectory Planning Method for Cruise Vehicles |
| YAO Jiangchuan1， ZHANG Mingen2， WANG Xiaogang1， E Bin1， CUI Naigang1 |
| 1. School of Aerospace Engineering， Harbin Institute of Technology， Harbin 150006， Heilongjiang， China；
2. Shanghai Electro-Mechanical Engineering Institute， Shanghai 201109， China |
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Abstract This paper proposed a Mercator transformation-based planning method for the online trajectory planning of cruise vehicles subject to no-fly zone constraints. By directly incorporating the planned trajectory's heading angle variation into the planning plane's higher-order derivatives, this approach explicitly characterised the energy expenditure of the trajectory without introducing dynamic constraints. The proposed method leverages quadratic programming (QP) optimisation properties to improve efficiency. It formulated the online trajectory planning problem under the QP framework, simultaneously addressing energy consumption and no-fly zone constraints. This formulation significantly enhanced computational efficiency and solution optimality. Simulation results demonstrate that the method can efficiently generate smooth, energy-efficient, and conveniently trackable trajectories while strictly complying with no-fly zone restrictions, achieving effective online trajectory planning for cruise vehicles.
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Received: 18 February 2025
Published: 15 July 2025
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| [1] |
SONG Rui, ZHANG Gang, LIU Siyu, WANG Shichao, QIN Jiaxing, YANG Yi. Cooperative Trajectory Planning for Multi-Near Space Vehicle in Glide Phase[J]. Air & Space Defense, 2025, 8(2): 66-76. |
| [2] |
LIN Zhaochen, ZHANG Xinran, LIU Ziyang, HE Fenghua, OUYANG Lei. Deep Learning-Based Hypersonic Vehicle Motion Behavior Recognition[J]. Air & Space Defense, 2024, 7(1): 48-55. |
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2025, Vol. 8 
