Pubblicazioni

Versione: 1.0 Approvato

LDO-ID 2021PUB00160

Titolo Towards Cognitive IRST

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.

Autori Andreoni, Alessandro; Conte, Roberto; Fortunato, Luca; Leoni, Andrea; Stellino, Flavio; Castaldo, Francesco

Tipologia Paper for Seminar/Symposium/Conference

Media SPIE Security + Defence Conference (13-17 September 2021, Online Only)

Sito web

https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11866/118660I/Towards-cognitive-IRST/10.1117/12.2600250.full?SSO=1

Anno 2021