biostudies-literatureGuo DNational Natural Science Foundation of China (National Science Foundation of China)633https://www.ebi.ac.uk/biostudies/studies/S-EPMC12816100biostudies-literatureUnknown17(1)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-sNature communicationsMulti-horizon flight trajectory prediction enabled by time-frequency wavelet transform.PMC128161006240138062371323Liu JZhang ZZhang JGuo DLin YfalseMulti-horizon flight trajectory prediction enabled by time-frequency wavelet transform.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-s2025-01-01T00:00:00Z2025 Dec2026-06-16T03:07:46.666Z2026-06-16T03:05:51.671ZS-EPMC128161004138157910.1038/s41467-025-67399-9