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Hierarchical fully adaptive radar
Author(s) -
Mitchell Adam E.,
Smith Graeme E.,
Bell Kristine L.,
Duly Andrew J.,
Rangaswamy Muralidhar
Publication year - 2018
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2018.5339
Subject(s) - radar , computer science , remote sensing , geology , telecommunications
By emulating the cognitive perception–action cycle believed to be at the core of animal cognition, cognitive radars promise to improve radar performance over standard systems. The fully adaptive radar (FAR) framework provides a generalised approach to implementing a single cognitive perception–action cycle for radar systems, but complex adaptive problems necessitate the interaction of multiple perception–action cycles. This study describes the general form of the hierarchical FAR (HFAR) framework. The HFAR framework is applied to a single‐target tracking, sensor fusion problem, and real‐time experimental results demonstrate the efficacy of the proposed architecture for handling problems of varying scales in a consistent, adaptive fashion.

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