Flight trajectory clustering based on a novel distance from a point to a segment set

2019 ◽  
Author(s):  
Yingchao Xiao ◽  
Yuanyuan Ma ◽  
Hui Ding ◽  
Qiucheng Xu
Keyword(s):  
Trajectory Clustering ◽  
Flight Trajectory

A Study on Estimation of Aircraft Interference Resolution Procedure by Surveillance-Derived Flight Trajectory

2015 ◽  
Vol 14 (0) ◽  
pp. 77-83 ◽  
Author(s):  
Tomoyuki KOZUKA ◽  
Yoshikazu MIYAZAWA ◽  
Navinda Kithmal WICKRAMASINGHE ◽  
Mark BROWN ◽  
Yutaka FUKUDA
Keyword(s):  
Flight Trajectory ◽  
Interference Resolution

Vehicle trajectory clustering based on 3D information via a coarse-to-fine strategy

2017 ◽  
Vol 22 (5) ◽  
pp. 1433-1444 ◽  
Author(s):  
Huansheng Song ◽  
Xuan Wang ◽  
Cui Hua ◽  
Weixing Wang ◽  
Qi Guan ◽  
...  
Keyword(s):  
Trajectory Clustering ◽  
Vehicle Trajectory ◽  
3D Information ◽  
Coarse To Fine

Trajectory shaping guidance law design using constraint-combining multiplier

2021 ◽  
pp. 095441002098637
Author(s):  
Min-Guk Seo ◽  
Chang-Hun Lee ◽  
Tae-Hun Kim
Keyword(s):  
Design Method ◽  
Impact Angle ◽  
State Variables ◽  
Flight Trajectory ◽  
Potential Significance ◽  
Guidance Law ◽  
Terminal Constraints ◽  
The Impact ◽  
Guidance Laws ◽  
Impact Angle Constraint

A new design method for trajectory shaping guidance laws with the impact angle constraint is proposed in this study. The basic idea is that the multiplier introduced to combine the equations for the terminal constraints is used to shape a flight trajectory as desired. To this end, the general form of impact angle control guidance (IACG) is first derived as a function of an arbitrary constraint-combining multiplier using the optimal control. We reveal that the constraint-combining multiplier satisfying the kinematics can be expressed as a function of state variables. From this result, the constraint-combining multiplier to achieve a desired trajectory can be obtained. Accordingly, when the desired trajectory is designed to satisfy the terminal constraints, the proposed method directly can provide a closed form of IACG laws that can achieve the desired trajectory. The potential significance of the proposed result is that various trajectory shaping IACG laws that can cope with various guidance goals can be readily determined compared to existing approaches. In this study, several examples are shown to validate the proposed method. The results also indicate that previous IACG laws belong to the subset of the proposed result. Finally, the characteristics of the proposed guidance laws are analyzed through numerical simulations.

scholarly journals A Survey on Applications of Reinforcement Learning in Flying Ad-Hoc Networks

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 449
Author(s):  
Sifat Rezwan ◽  
Wooyeol Choi
Keyword(s):  
Reinforcement Learning ◽  
Ad Hoc Networks ◽  
Wireless Ad Hoc Networks ◽  
Routing Protocol ◽  
Traffic Congestion ◽  
Ad Hoc ◽  
High Mobility ◽  
Flight Trajectory ◽  
Research Issues ◽  
Hoc Networks

Flying ad-hoc networks (FANET) are one of the most important branches of wireless ad-hoc networks, consisting of multiple unmanned air vehicles (UAVs) performing assigned tasks and communicating with each other. Nowadays FANETs are being used for commercial and civilian applications such as handling traffic congestion, remote data collection, remote sensing, network relaying, and delivering products. However, there are some major challenges, such as adaptive routing protocols, flight trajectory selection, energy limitations, charging, and autonomous deployment that need to be addressed in FANETs. Several researchers have been working for the last few years to resolve these problems. The main obstacles are the high mobility and unpredictable changes in the topology of FANETs. Hence, many researchers have introduced reinforcement learning (RL) algorithms in FANETs to overcome these shortcomings. In this study, we comprehensively surveyed and qualitatively compared the applications of RL in different scenarios of FANETs such as routing protocol, flight trajectory selection, relaying, and charging. We also discuss open research issues that can provide researchers with clear and direct insights for further research.

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