Nano-drones, are insect-like size drones with a capability of intrusion to provide intelligence and potentially violate secure establishments and public privacy rights. Nanodrones are already an existing technology which is becoming more and more available, portable, affordable and easily operated. As such, they may soon become a plausible defence and security threat. This paper presents the design and development of a K-Band FMCW radar prototype for nanodrone detection. The FMCW radar prototype consists of connectorised components operating at a carrier frequency of 24 GHz and offer high parameter selection flexibility. Experiments have been carried out in order to evaluate the system performance. Results show that a small Arcade PICO Drone Nano Quadcopter (smaller than 5 cm) could be detected, and that its micro-Doppler signature could be extracted from data.

Detection and classification of nano-targets (less than 5 cm in size) are becoming important technical challenges as nano-targets are largely invisible to conventional radar. Nano-drones, for example, may soon become a tangible threat capable of providing short-range stealthy surveillance. Similarly, insect pests are posing a significant agricultural risk by causing crop losses and subsequently reducing the yields. Frequency Modulated Continuous Wave (FMCW) radar is a technology that can provide short-range detection, with no blind range and very high resolution, at a relatively low cost. This paper presents the latest results of an ongoing project aiming at designing and developing a low-cost and bespoke 24 GHz FMCW radar prototype to enable detection of nano-targets and extract their Doppler signatures. A home-brew S-band FMCW radar prototype has been initially designed and developed, using off-the-shelf components, to demonstrate the feasibility of our proposed design solution and inform all future activities at 24 GHz. Several experiments have been carried out to test the Sband prototype and assess its performance against larger drones and cars. Results have shown targets could be successfully detected and their micro-Doppler signatures extracted using Short-Time Fourier Transform (STFT) techniques.

One of the challenges of the Internet of Things (IoT) is to provide connectivity to devices around the globe. Long Range (LoRa) is one of the most practical technologies due to its low-power and long-range capabilities to be used by the Low Earth Orbit (LEO) CubeSat. This study aims to evaluate the performance of the Long Range Wide Area Network (LoRaWAN) in receiving uplink messages from ground sensor nodes at an altitude of 550 km with a maximum elevation angle of 0°. An Adaptive Data Rate (ADR) is applied for the dynamic signal reception with respect to receiving signal strength. In this study, the path loss is simulated using attenuation levels from 30–150 dB to ensure that the signal connectivity success rate is at a minimum elevation angle and to perform the link analysis under various conditions. The results show that the LoRaWAN signals are successfully received with an SNR of −21 at the 150 dB attenuation from the end nodes because of its spread-spectrum technique which allows the system to detect signals under the noise floor.