Abstract

With the increased push for spectrum sharing techniques, the technological world surrounding radar has been constantly pushing to find new methodologies. From being able to integrate with a communication system to mitigating the effects of other users on a system, the research community is pushing forward. We look to tackle the problem of mitigating a jammer using a multipath MUltiple SIgnal Classification (MUSIC) based approach. We take multiple steps to implement this and generate a framework for future work. We first take a look at understanding the current state of the art research surrounding DFRC, multipath exploitation, MUSIC algorithms, RIS and more. We then delve into the factors affecting MUSIC Algorithm performance, followed with a machine learning approach to classification of jammer presence. We then close by proposing a model to mitigate a jammer using the multipath in an urban environment. We show a near 99\% success rate in classification using a decision tree and also show a successful estimation of a jammers coordinate using multipath MUSIC and successful mitigation to uncover our original target. The ultimate purpose of this is to build a framework which will be built upon in the future for jammer mitigation.

Publication Date

1-10-2026

Document Type

Thesis

Student Type

Graduate

Degree Name

Electrical Engineering (MS)

Department, Program, or Center

Electrical and Microelectronic Engineering, Department of

College

Kate Gleason College of Engineering

Advisor

Alireza Vahid

Advisor/Committee Member

Sohail Dianat

Advisor/Committee Member

Gill Tsouri

Campus

RIT – Main Campus

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