A predictive guidance scheme for pursuit-evasion engagements

M. Ugur Akcal, Girish Chowdhary

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This work develops a predictive pursuer guidance algorithm that generates sub-optimal guidance commands based on evader acceleration predictions produced by a recurrent neural network. Due to their reactive nature, common guidance laws such as proportional navigation (PN) or augmented proportional navigation (APN) have either restricted capture region or poor engagement performance against highly maneuverable evader. On the other hand, even though predictive guidance laws tend to have better performance against highly maneuverable evaders, they assume full or partial knowledge of the evader dynamics, which can be a limiting assumption. To address aforementioned shortcomings of the previous efforts, this paper proposes a pursuer guidance algorithm in which the evader’s future acceleration commands are predicted in a finite time horizon by employing a network of gated recurrent units (GRU), which are trained on a library of exemplary evader dynamics. Predicted evader commands are then assigned within the constraints of a transcribed finite-horizon optimal control problem, cast as a nonlinear program (NLP). Once the NLP is solved over a finite time horizon, the pursuer acceleration solution for the next time step is considered as the pursuer guidance command. Simulation studies are conducted for interception of an agile evasive evader to compare the current work against the conventional laws mentioned above and a modern counterpart. Results demonstrate that the proposed guidance law is superior to compared approaches in terms of guidance performance metrics such as miss distance.

Original languageEnglish (US)
Title of host publicationAIAA Scitech 2021 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
Number of pages15
ISBN (Print)9781624106095
StatePublished - 2021
EventAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021 - Virtual, Online
Duration: Jan 11 2021Jan 15 2021

Publication series

NameAIAA Scitech 2021 Forum
Volume1 PartF


ConferenceAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021
CityVirtual, Online

ASJC Scopus subject areas

  • Aerospace Engineering


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