Multi-horizon flight trajectory prediction enabled by time-frequency wavelet transform.

ABSTRACT: Flight trajectory prediction is a fundamental task in air traffic control. While our previous WTFTP framework leveraged wavelet-based time-frequency analysis for trajectory prediction, its iterative single-horizon paradigm suffers from error accumulation in long-horizon forecasts. Here, the WTFTP+ framework is proposed to enhance multi-horizon prediction performance while further exploring the potential of time-frequency analysis in flight trajectory prediction tasks. An encoder-decoder neural architecture is designed to generate wavelet components of predicted trajectories, where a direct multi-horizon prediction paradigm is employed to mitigate the cumulative errors of the WTFTP. Additionally, a time-frequency bridging mechanism is proposed to explore intrinsic correlations among multi-s

SUBMITTER: Guo D 

PROVIDER: S-EPMC12816100 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature