Emerging Trends in Radar: Metacognitive Radar Networks for the Next Generation of Intelligent Sensing

This article highlights the emerging area of metacognitive radar. The metacognitive radar uses models that leverage concepts from human learning to form an outer feedback and control loop for cognitive radar. Thus, metacognitive radar monitors the performance of cognitive radar through an exploration and exploitation reinforcement learning process. This article provides an overview of cognitive and metacognitive radar systems, along with a discussion of sensor development for spectrum sharing due to its strong role in many cognitive radar system designs. Metacognition for network radar is also discussed in the context of game theory and network reinforcement learning. Elements of a proposed metacognitive radar network are introduced, and several future research challenges are discussed.

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Publication Details

Journal
IEEE Aerospace and Electronic Systems Magazine
Published
2025-02-07
DOI
https://doi.org/10.1109/maes.2025.3539607
Citations
3
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
14.98
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article

Emerging Trends in Radar: Metacognitive Radar Networks for the Next Generation of Intelligent Sensing

R. Michael Buehrer, Anthony F. Martone, David M. McNamara
3 citations
IEEE Aerospace and Electronic Systems Magazine
Radar Systems and Signal Processing
14.98
article

Emerging Trends in Radar: Metacognitive Radar Networks for the Next Generation of Intelligent Sensing

R. Michael Buehrer, Anthony F. Martone, David M. McNamara
article en
3 citations

Abstract

This article highlights the emerging area of metacognitive radar. The metacognitive radar uses models that leverage concepts from human learning to form an outer feedback and control loop for cognitive radar. Thus, metacognitive radar monitors the performance of cognitive radar through an exploration and exploitation reinforcement learning process. This article provides an overview of cognitive and metacognitive radar systems, along with a discussion of sensor development for spectrum sharing due to its strong role in many cognitive radar system designs. Metacognition for network radar is also discussed in the context of game theory and network reinforcement learning. Elements of a proposed metacognitive radar network are introduced, and several future research challenges are discussed.

IEEE Aerospace and Electronic Systems MagazineVol. 40(6)
DEVCOM Army Research Laboratory (US), United States Army Combat Capabilities Development Command (US), Virginia Tech (US)
Reduced inequalities
Openalex Percentile: Top 2%
Radar Systems and Signal Processing
14.98
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