Resource management in active-passive multifunction radar networks

Despite the extensive research within the field of resource management in monostatic multifunction radar, the resource management techniques for a multifunction radar network are still in their infancy. More specifically, a network which has the ability to switch modes between monostatic and bistati...

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Bibliographic Details
Main Author: Sherwani, Hashir
Published: University College London (University of London) 2018
Subjects:
Online Access:https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.756353
Description
Summary:Despite the extensive research within the field of resource management in monostatic multifunction radar, the resource management techniques for a multifunction radar network are still in their infancy. More specifically, a network which has the ability to switch modes between monostatic and bistatic configuration may potentially be able to capitalise on the advantages of both configurations. This is a gap which has been identified and is the aim of this thesis to explore. The research within this thesis begins by exploring the advantages provided by a bistatic configuration over a monostatic configuration. The conclusions from the initial research are carried forward to design a complete resource management framework for a multifunction radar network consisting of active and passive nodes. The resource management framework is broken into two sub-problems, resourceallocation and the scheduling problem. The resource-allocation problem deals with the task parameter selection methodology to optimally distribute the finite resources. This incorporates the concept of information sharing, which can be considered as a subset of information fusion theory, to delegate a given task to the best suited sensor within the network. A Quality of service framework is utilised to solve the resource-allocation problem where the resulting algorithm is referred to as APNQ-RAM. The scheduling problem is solved by deploying an earliest deadline first scheduler on master-slave architecture where the resulting algorithm is named as MS-EDFS. The research has also explored the impact of the networks geometry and the number of nodes on the network’s performance in tracking and surveillance functions. The research shows significant advantages in terms of tracking and surveillance performance provided by such a network in comparison to a monostatic configuration functioning on its own.