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Unmanned Aircraft Systems (UAS) are being used commonly for video surveillance, providing valuable video data and reducing the risks associated with human operators. Thanks to its benefits, the UAS traffic is nearly doubling every year. However, the risks associated with the UAS are also growing. According to the FAA, the volume of air traffic will grow steadily, doubling in the next 20 years. Paired with the exponential growth of the UAS traffic, the risk of collision is also growing as well as privacy concerns. An effective UAS detection and/or tracking method is critically needed for air traffic safety. This research is aimed at developing a system that can identify/detect a UAS, which will subsequently enable counter measures against UAS. The proposed system will identify a UAS through various methods including image processing and mechanical tracking. Once a UAS is detected, a countermeasure can be employed along with the tracking system. In this research, we describe the design, algorithms, and implementation details of the system as well as some performance aspects. The proposed system will help keep the malicious or harmful UAS away from the restricted or residential areas.
Ganti et al. (Wed,) studied this question.