Towards cognitive IRST

R. Conte; F. Castaldo; A. Leoni; F. Stellino; A. Andreoni; L. Fortunato

doi:10.1117/12.2600250

12 September 2021 Towards cognitive IRST

R. Conte, F. Castaldo, A. Leoni, F. Stellino, A. Andreoni, L. Fortunato

Proceedings Volume 11866, Electro-Optical and Infrared Systems: Technology and Applications XVIII and Electro-Optical Remote Sensing XV; 118660I (2021) https://doi.org/10.1117/12.2600250
Event: SPIE Security + Defence, 2021, Online Only

Abstract

Cognitive radar systems adapt processing, receiver and transmitted waveform parameters by continuously learning and interacting with the operative environment. IRST systems are passive; as such no RF emission is involved. Nevertheless, the cognitive paradigm can be applied to passive sensors in order to optimize operational modes choice, platform and processing parameters on the fly. A cognitive based IRST, while enhancing the overall performance of the system, would also reduce the crew workload during the mission. In this paper, steps and challenge toward cognitive IRST are described, along with a proof-of-concept example of improved tracking capabilities using reinforcement learning methods.

Conference Presentation

Citation Download Citation

R. Conte, F. Castaldo, A. Leoni, F. Stellino, A. Andreoni, and L. Fortunato "Towards cognitive IRST", Proc. SPIE 11866, Electro-Optical and Infrared Systems: Technology and Applications XVIII and Electro-Optical Remote Sensing XV, 118660I (12 September 2021); https://doi.org/10.1117/12.2600250

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