Abstract
Unmanned Aerial Vehicles (UAVs) are widely available in the current market to be used either for recreation as a hobby or to serve specific industrial requirements, such as agriculture and construction. However, illegitimate and criminal usage of UAVs is also on the rise which introduces their effective identification and detection as a research challenge. This paper proposes a novel machine learning-based for efficient identification and detection of UAVs. Specifically, an improved UAV identification and detection approach is presented using an ensemble learning based on the hierarchical concept, along with pre-processing and feature extraction stages for the Radio Frequency (RF) data. Filtering is applied on the RF signals in the detection approach to improve the output. This approach consists of four classifiers and they are working in a hierarchical way. The sample will pass the first classifier to check the availability of the UAV, and then it will specify the type of the detected UAV using the second classifier. The last two classifiers will handle the sample that is related to Bebop and AR to specify their mode. Evaluation of the proposed approach with publicly available dataset demonstrates better efficiency compared to existing detection systems in the literature. It has the ability to investigate whether a UAV is flying within the area or not, and it can directly identify the type of UAV and then the flight mode of the detected UAV with accuracy around 99%.
Highlights
In modern society and starting from this century, Unmanned Aerial Vehicles (UAVs), or drones, are widely used around the world
We present the pre-processing tasks to get a cleaned data, which is suitable to be used in the learning approach directly
We show the representation of the Radio Frequency (RF) data in time and frequency domain for some of the selected UAV modes
Summary
In modern society and starting from this century, Unmanned Aerial Vehicles (UAVs), or drones, are widely used around the world. The recent popularity of UAVs is primarily due to the progress in developing the precision sensors, such as gyroscopes and motion sensors, which are employed to guide, navigate and control the UAVs for tracking and observation purposes in the candidate region. UAVs were first used by the military especially in the photogrammetry and 3D scanning for tracking and surveillance purposes, as in References [1,2,3]. Different civilian applications, including UAV photogrammetry, were developed, due to their low operating altitude, which can provide a high space resolution data [4,5]. The relative low cost of the UAV-based systems in many areas has earned considerable success. UAVs are used in multiple areas, including tracking, search and rescue tasks, package delivery, smart policing, video recording, and precision agriculture [6,7]. In view of emerging trends in UAV technologies, UAVs are expected to become an integral part in the modern technologies
Sign-in/Register to view highlights & summary 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.
