Abstract
In the last years, the commercial drone/unmanned aerial vehicles market has grown due to their technological performances (provided by the multiple onboard available sensors), low price, and ease of use. Being very attractive for an increasing number of applications, their presence represents a major issue for public or classified areas with a special status, because of the rising number of incidents. Our paper proposes a new approach for the drone movement detection and characterization based on the ultra-wide band (UWB) sensing system and advanced signal processing methods. This approach characterizes the movement of the drone using classical methods such as correlation, envelope detection, time-scale analysis, but also a new method, the recurrence plot analysis. The obtained results are compared in terms of movement map accuracy and required computation time in order to offer a future starting point for the drone intrusion detection.
Highlights
Considering their variety and the boundless applications in which they can be involved, the research interest in the drone field has grown exponentially in recent years
Considering the LSS unmanned aerial vehicles (UAV) intrusion challenges and the different methods previously presented, this paper proposes a new approach for the UAV/drone movement detection and characterization based on ultra-wide band (UWB) sensing
Due to its weight and dimensions, the drone is classified as micro UAV [37]
Summary
Angela Digulescu 1,2, *, Cristina Despina-Stoian 1,3 , Denis Stănescu 1,2 , Florin Popescu 1 , Florin Enache 1 , Cornel Ioana 2 , Emanuel Rădoi 3 , Iulian Rîncu 1 and Alexandru S, erbănescu 1.
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