Drone RCS Statistical Behaviour and Its Implications for Agriculture Drones Air Traffic Management

Abstract

This paper explores UAS (copter-type drone) radar cross-section behaviour impacting drone traffic control support by independent surveillance. The proliferation of drone traffic worldwide includes agriculture and state challenges in airspace safety. Dependent surveillance based on data communication is susceptive to cyber-attacks and should be augmented by more reliable methods. Primary radars are capable of providing relevant data for safety enforcement. Radar observation is challenged by small RCSs, influenced by copter flight behaviour. The paper further presents the measurement and analysis results of several UAV Radar Cross Sections (RCS), focusing on different flight parameters, such as pitch and roll. Understanding RCS statistical behaviour is crucial for primary radar drone detection. Insights into RCS fluctuations can enhance drone surveillance and drone traffic control for agricultural applications.