Detection, identification and localization of R/C electronic devices through their unintended emissions

"The accurate and reliable detection of unintended emissions from radio receivers has a broad range of commercial and security applications. This thesis presents detection, identification, and localization methods for multiple RC electronic devices in a realistic environment. First, a Hurst parameter based detection method for super-regenerative receivers (SRR) has been used for detection. Hurst parameter based detection method exploits a self-similarity property of the SRR receiver emissions to distinguish it from background noise. Second paper presents a novel detection and localization scheme of multiple RC electronic devices called Edge-Synthetic Aperture Radar (Edge-SAR). It employs cost-effective, mobile antenna-array detectors. Two types of RC devices are considered: SRR with H parameter method and super heterodyne receivers (SHR) with peak detection method. Third paper improves detection of multiple devices by proposing a dynamic antenna-array processing method called VIVEK-MVDR-GA. It combines multi-constrained genetic algorithm (GA) and minimum variance distortion-less response (MVDR) method to increase accuracy of detection and localization of multiple devices. Finally, a 4-element array mounted on an unmanned aerial vehicle (UAV) is proposed to overcome multipath and reflection due to environmental surroundings and improve the response time in compromised scenarios. Also, a time based correlation method is proposed for array detectors to identify the line of sight (LOS) and non-line of sight (N-LOS) signals. A normalized error correlation function has been implemented to improve the estimation of angle of arrival (AOA) in the presence of strong non-line of sight (N-LOS) signals"--Abstract, page iv.

Name thesis:degree_name

Ph. D. in Electrical Engineering

Grantor

Missouri University of Science and Technology

Author dc:creator

• Thotla, Vivek

• Detection
• Identification
• Localization
• R/C devices
• Electrical and Computer Engineering

Repository record dc:identifier

https://scholarsmine.mst.edu/doctoral_dissertations/2604

OAI identifier oai:identifier

oai:scholarsmine.mst.edu:doctoral_dissertations-3609