Print Email Facebook Twitter Spoofing detection in a loosely coupled GNSS and IMU system via Synthetic Arrays Title Spoofing detection in a loosely coupled GNSS and IMU system via Synthetic Arrays Author Biserkov, Kostadin (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor van der Veen, Alle-Jan (mentor) Uysal, Faruk (mentor) Bos, Andre (mentor) Degree granting institution Delft University of Technology Date 2019-08-20 Abstract With the ever-expanding need for accuracy in the world of navigation, Global Navigation Satellite Systems(GNSS) such as GPS and Galileo have become the primary option around the world. As such, the potential damage that can be caused by malicious tampering with the receivers continues to grow. One such threat, known as Spoofing, comprises of transmission of altered GNSS signals to a target receiver(s). This process leads to false positional and/or time data on the receiver's end. Spoofing has been a topic of discussion for roughly two decades. With many theoretical approaches to its detection, this work focuses on the Angle of Arrival technique via the construction of a synthetic array from a single moving element, aided by positional information provided by Inertial Measurement Unit (IMU). This method relies on the periodic nature of the L1 signal, and focuses primarily on the case of GPS as an example. Using simulation and sample data, the possibility and limitations of constructing virtual antenna arrays is explored. It is shown that despite being viable for low number of sources during the simulation, the complexity of signal propagation within the real world implementation of GNSS system renders this technique inoperable in its first iteration. Subject GNSSSpoofingIMUSynthetic arrays To reference this document use: http://resolver.tudelft.nl/uuid:3d48f0f2-259f-42e8-bf18-689270f53a10 Part of collection Student theses Document type master thesis Rights © 2019 Kostadin Biserkov Files PDF Spoofing_detection_in_a_l ... Arrays.pdf 5.3 MB Close viewer /islandora/object/uuid:3d48f0f2-259f-42e8-bf18-689270f53a10/datastream/OBJ/view