Adaptive Beamsteering Cognitive Radar with Integrated Search-and-Track of Swarm Targets
MetadataShow full item record
Adaptive beamsteering cognitive radar (AB-CRr) systems seek to improve detection and tracking performance by formulating a beam placement strategy adapted to their environment. 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 work, 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. As a result, a list of newly CRr-integrated contributions are enumerated: a) improved uncertainty function design, b) incorporates Mahalanobis nearest neighbors multi-target association methodology into AB-CRr, c) introduces a novel Kalman-based consolidated swarm tracking methodology with a common velocity state vector that frames targets as a correlated collection of swarm members, d) introduces an improved uncertainty growth model for updating environment probability map, e) introduces a method for incorporating estimated swarm structure and behavior into the uncertainty update model referred to as "track hinting", and f) introduces new metrics for swarm search/detection and tracking called swarm centroid track error and swarm tracking dwell ratio. The results demonstrate that AB-CRr is capable of adapting its beamsteering strategy to efficiently perform resource balancing between target search and swarm tracking applications, while taking advantage of group structure and intra-swarm target correlation to resist large swarms overloading available resources.
The article of record as published may be found at http://dx.doi.org/10.1109/ACCESS.2021.3069350, IEEE Access
RightsThis 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.
Showing items related by title, author, creator and subject.
Evangelista, Paul F.; Darken, Christian J.; Jungkunz, Patrick (2011);Representation of search and target acquisition (STA) in military models and simulations arguably abstracts the most critical aspects of combat. This research focuses on the search aspect of STA for the unaided human eye. ...
Lim, Jun Jie (Monterey, CA; Naval Postgraduate School, 2018-09);Target tracking and monitoring plays a crucial role in the intelligence collection domain. With the advancement of intelligence collection and data analysis methods, we can sometimes obtain a target’s initial and end ...
Williams, John Walter. (Monterey, California. Naval Postgraduate School, 1988);This thesis is a study of missile and target parameters used in second and third order modeling of the tracking subsystem used in radar guided guided missiles. Guidance methods are analyzed to determine which method is ...