Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3775
Title: Intruder Drone Detection using Unmanned Aerial Vehicle Borne Radar (UAVBR) via Reconfigurable Intelligent Reflective Surface (IRS)
Authors: Mandal, Priti
Roy, Lakshi Prosad
Das, Santos Kumar
Keywords: Intruder Drone
UAVBR
Reconfigurable IRS
Detection
Issue Date: Nov-2022
Citation: IEEE 19th India Council International Conference (INDICON), Kochi, Kerala, 24th - 26th November 2022
Abstract: Easy availability of the Drones/Unmanned Aerial Vehicles (UAVs) may lead to a carping situation. This makes it important to detect the presence of the Intruder drone in any particular area. Towards this matter, work is taken up on detection of intruder drone using UAV Borne Radar (UAVBR) via Reconfigurable Intelligent Reflective Surface (IRS). Direct Line of Sight (LoS) scenario may occur while detection of intruder drone but signal may be weak. So, to increase the probability of detection of intruder drone Reconfigurable IRS is used with various pattern of IRS such as Uniform Linear Array (ULA), Uniform Rectangular Array (URA) and Uniform Circular Array (UCA). Further, performance analysis is done by considering different parameters in Matlab software.
Description: Copyright belongs to proceeding publisher
URI: http://hdl.handle.net/2080/3775
Appears in Collections:Conference Papers

Files in This Item:
File Description SizeFormat 
2022_INDICON_SKDas_Intruder.pdf738.99 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.