Abstract
Improvised explosive devices (IEDs) have recently become a considerable national security concern for governments due to their increased use. Since IEDs do not have a particular shape, detecting and classifying IEDs becomes a complex problem. Due to the irregularity of the wire shape, recent research focuses on detecting command wire, which is the triggering mechanism in IEDs. This study proposes a detection and clustering algorithm for wire detection. The synthetic data were generated using the gprMax software, an open-source Finite-Difference Time-Domain (FDTD) simulation environment. Different wire and clutter orientations were simulated while creating a 2D GPR database. Three different prescreening algorithms are compared concerning computational time and signal-to-noise ratio. The Go Decomposition (GoDec) method was used at the preprocessing stage. Discriminating the buried wire from clutter was conducted using the k-means clustering method. The proposed algorithm results show promising outcomes over simulated GPR 2D C-scans.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
