WGAN-GP and LSTM based Prediction Model for Aircraft 4- D Traj ectory

Lei Zhang, Huiping Chen, Peiyan Jia, Zhihong Tian, Xiaojiang Du

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

The rapid growth of air traffic flow has brought the airspace capacity close to saturation and, at the same time, has resulted in great stress for air traffic controllers. The 4- D trajectory-based operation system is an important solution to problems in the current civil aviation field. The system mainly relies on accurate 4-D trajectory prediction technology to share trajectory information among air traffic control, airlines, and aircraft to achieve coordinated decision-making between flight and control. However, due to the complexity of trajectory data processing, the current 4-D trajectory prediction technology cannot meet actual needs. Therefore, a data generation and prediction network model (DGPNM) is proposed. It integrates the Wasserstein generative adversarial networks with gradient penalty (WGAN-GP) and long-short-term memory (LSTM) neu-ral networks. With its outstanding performance, the LSTM neural network is utilized in both the generation module and the prediction module. The proposed model generates plenty of sample data to enlarge the train set, so overfitting could be reduced in the process of LSTM training. Experimental results prove that compared with other classical methods, the altitude prediction accuracy in the proposed model far exceeds that in current research results, which improves the prediction accuracy of the 4- D trajectory.

Original languageEnglish
Title of host publication2022 International Wireless Communications and Mobile Computing, IWCMC 2022
Pages937-942
Number of pages6
ISBN (Electronic)9781665467490
DOIs
StatePublished - 2022
Event18th IEEE International Wireless Communications and Mobile Computing, IWCMC 2022 - Dubrovnik, Croatia
Duration: 30 May 20223 Jun 2022

Publication series

Name2022 International Wireless Communications and Mobile Computing, IWCMC 2022

Conference

Conference18th IEEE International Wireless Communications and Mobile Computing, IWCMC 2022
Country/TerritoryCroatia
CityDubrovnik
Period30/05/223/06/22

Keywords

  • LSTM neural network
  • WGAN-GP
  • traffic flow
  • trajectory prediction

Fingerprint

Dive into the research topics of 'WGAN-GP and LSTM based Prediction Model for Aircraft 4- D Traj ectory'. Together they form a unique fingerprint.

Cite this