ADAPTIVE BEAMSTEERING COGNITIVE RADAR WITH INTEGRATED SEARCH-AND-TRACK OF SWARM TARGETS
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Authors
Johnson, Zachary W.
Subjects
cognitive radar
adaptive beamsteering
adaptive beamsteering
Advisors
Romero, Ric
Date of Issue
2020-06
Date
June 2020
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
Unlike traditional radar systems, cognitive radars are designed to employ a perception-action cycle to
continuously adapt to their environment. Adaptive beamsteering cognitive radar (AB-CRr) systems seek to
improve detection and tracking performance by formulating a beam placement strategy adapted to their
environment. Rather than employing traditional raster scanning in a search-scene, AB-CRr builds a
probabilistic model of the target environment that enables it to more efficiently employ its limited resources
to locate and track targets. In this thesis, we investigate methods for adapting the AB-CRr framework to
detect and track large target swarms. This is achieved by integrating the properties of correlated-motion
swarms into both the radar tracking model and AB-CRr’s underlying dynamic probability model. The results
demonstrate that AB-CRr is capable of adapting its beamsteering strategy to efficiently perform resource
balancing between search and tracking applications, while taking advantage of group structure and
intra-swarm target correlation to resist large swarms overloading available resources.
Type
Thesis
Description
Series/Report No
Department
Electrical and Computer Engineering (ECE)
Organization
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NPS Report Number
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Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.