Electric Field Characteristics and an Electrostatic Detection Method for Small UAVs Based on Triboelectric Charging

The widespread use of small unmanned aerial vehicles (UAVs) has increased the need for reliable short-range detection in complex environments. Interactions between the vehicle surface, air, and suspended particles can accumulate charge and generate an electrostatic field, providing a passive signature independent of external radiation. This study develops a quantitative triboelectric charging model based on kinetic gas theory. A shielded high-speed airflow impact experiment estimated an equivalent charge-transfer parameter for the tested carbon-fiber composite and airflow, with an adjusted coefficient of determination (adjusted R2) of 0.967. Flow-field, dilute gas–solid two-phase, and multiphysics electrostatic simulations were then used to determine surface charging and near-field characteristics. Flight encounter tests employed an induced-current electrostatic detector and a MEMS electric-field sensor. At 30 m/s, the simplified model predicted a total charge on the order of 10−7 C and a 3.8% variation from 0° to 20° angle of attack. The maximum electric-field strength along the nominal 10 m encounter trajectory was 415 V/m. After filtering and temporal alignment, the measured and simulated electric-field rates of change had an adjusted R2 of 0.980 for the selected encounter, while the MEMS measurements yielded a shape-consistency coefficient of 0.937. The encounter measurements provide preliminary support for the predicted response trend under the tested conditions and a quantitative framework for analyzing the electrostatic near-field signatures and passive detection of small UAVs. The method may serve as a complementary means of short-range UAV detection.