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MS Thesis - Jayson Rook - REVISED 2023.pdf (1.9 MB)
ETD Abstract Container
Abstract Header
Detecting Anomalous Behavior in Radar Data
Author Info
Rook, Jayson Carr
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=miami1622205414960438
Abstract Details
Year and Degree
2021, Master of Science, Miami University, Computational Science and Engineering.
Abstract
This project seeks to investigate and apply anomaly detection algorithms for a wideband receiver, that will flag anomalous radar behaviors sent by some transmitter external to the receiver's system. Flagging these anomalies will indicate to the receiver system that the radar's behavior has been reprogrammed, knowledge which is important for determining optimal countermeasures. The programs developed have investigated several approaches to accomplish this. Firstly, clustering methods like DBSCAN can group the observed pulses into distinct classes, reducing the problem to finding disruptions in patterns of numerical labels. Semi-supervised techniques like Hidden Markov Models and Long Short-Term Memories can be applied to learn these patterns for normal behavior and flag anomalies where the patterns are broken. Lastly, an unsupervised technique based on cross-correlations takes an alternative approach of flagging all the different behaviors in a sequence, without any initial training. Simulation results on test data demonstrate the functionality of these techniques, which are offered as potential suggestions for implementation in a real system.
Committee
Chi-Hao Cheng, Ph.D. (Advisor)
Dmitriy Garmatyuk, Ph.D. (Committee Member)
Mark Scott, Ph.D. (Committee Member)
Pages
53 p.
Subject Headings
Computer Engineering
;
Computer Science
;
Electrical Engineering
;
Remote Sensing
Keywords
Electronic Warfare
;
Electronic Countermeasure
;
Multifunction Radar
;
Anomaly Detection
;
Hidden Markov Model
;
Long Short-Term Memory
;
Pattern Detection
;
Cross-Correlation
;
Overlapping Index
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Refworks
EndNote
RIS
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Citations
Rook, J. C. (2021).
Detecting Anomalous Behavior in Radar Data
[Master's thesis, Miami University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=miami1622205414960438
APA Style (7th edition)
Rook, Jayson.
Detecting Anomalous Behavior in Radar Data.
2021. Miami University, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=miami1622205414960438.
MLA Style (8th edition)
Rook, Jayson. "Detecting Anomalous Behavior in Radar Data." Master's thesis, Miami University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=miami1622205414960438
Chicago Manual of Style (17th edition)
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Document number:
miami1622205414960438
Download Count:
326
Copyright Info
© 2021, some rights reserved.
Detecting Anomalous Behavior in Radar Data by Jayson Carr Rook is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Miami University and OhioLINK.