In recent years, the use of Flying drones and modern Unmanned aerial vehicles (UAVs) with the latest techniques and capabilities for both civilian and military applications growing sustainably on a large scope, Drones could autonomously fly in several environments and locations and could perform various missions, providing a system for UAV detection and tracking represent crucial importance. This paper discusses Designing Detection and Tracking method as a part of Aero-vehicle Defense System (ADS) for UAVs using Deep learning algorithms. The small Radar cross-section (RCS) foot-print makes a problem for Traditional methods and Aero-vehicle Defense systems to distinguish between birds, stealth fighters, and UAVs incomparable of size and RCS characteristics, the detection is a challenge in low RCS targets because the chance of detection is incredibly less moreover, in the existence of interference and clutter which reduce the performance of detection process rapidly.