A novel voltage mode first order active only tuneable all pass filter (AOTAPF) circuit configuration is presented. The AOTAPF has been designed using ±0.7 V, 16 nm carbon nanotube field effect transistor (CNFET) Technology. The circuit uses CNFET based varactor and unity gain inverting amplifier (UGIA). The presented AOTAPF is realized with three N-type CNFETs and without any external passive components. It is to be noted that the realized circuit uses only two CNFETs between its supply-rails and thus, suitable for low-voltage operation. The electronic tunability is achieved by varying the voltage controlled capacitance of the employed CNFET varactor. By altering the varactor tuning voltage, a wide tunable range of pole frequency between 34.2 GHz to 56.9 GHz is achieved. The proposed circuit does not need any matching constraint and is suitable for multi-GHz frequency applications. The presented AOTAPF performance is substantiated with HSPICE simulation program for 16 nm technology-node, using the well-known Stanford CNFET model. AOTAPF simulation results verify the theory for a wide frequency-range.

Moving target detection is the most common task for Unmanned Aerial Vehicle (UAV) to find and track object of interest from a bird’s eye view in mobile aerial surveillance for civilian applications such as search and rescue operation. The complex detection algorithm can be implemented in a real-time embedded system using Field Programmable Gate Array (FPGA). This paper presents the development of real-time moving target detection System-on-Chip (SoC) using FPGA for deployment on a UAV. The detection algorithm utilizes area-based image registration technique which includes motion estimation and object segmentation processes. The moving target detection system has been prototyped on a low-cost Terasic DE2-115 board mounted with TRDB-D5M camera. The system consists of Nios II processor and stream-oriented dedicated hardware accelerators running at 100 MHz clock rate, achieving 30-frame per second processing speed for 640 × 480 pixels’ resolution greyscale videos.