INVESTIGATION OF RF SIGNATURE CHARACTERISTICS FOR UNMANNED AERIAL VEHICLES

Abstract

The features of radio-frequency (RF) signature formation of unmanned aerial vehicles (UAVs) were analyzed, and the main factors influencing their structure and informativeness were identified. Methods for determining signatures based on the analysis of electromagnetic wave scattering in different frequency ranges are considered, and the dependence of signatures on object geometry and material properties is investigated. The RF background of UAVs is analyzed as a combination of intrinsic electromagnetic emissions of control, telemetry, and data transmission channels. Temporal characteristics of signals are considered, including inter-packet intervals, statistical parameters, and autocorrelation properties of sequences used as additional identification features. The signal activity index and entropy-based characteristics are introduced for quantitative evaluation of signal intensity and structural complexity. Changes in RF signature parameters depending on UAV flight phases, including idle, pre-flight, active flight, hovering, autonomous operation, and landing, are analyzed. It is established that each operational mode corresponds to a characteristic combination of transmission frequency, signal power, and temporal structure, forming unique signature features. Approaches to generating equivalent signatures using passive and active methods are considered, including the application of DRFM and SDR technologies. Implementation methods of signature generation devices based on modern communication protocols such as LoRa, DSSS/CDMA, ExpressLRS, and Crossfire, as well as methods for generating synthetic temporal signal sequences, are analyzed. Graphical and diagram-based representations of RF signature variation depending on UAV operational modes are presented, with a detailed description of signal parameter dependencies.

Keywords: Unmanned aerial vehicles, UAV RF signature, UAV radio-frequency analysis, UAV identification, UAV detection