Compact-Range RCS Measurements and Modeling of Small Drones at 15 GHz and 25 GHz

TL;DR

This study presents a compact-range measurement method for small drone RCS at 15 GHz and 25 GHz, revealing frequency-dependent variations and modeling the RCS data with the generalized extreme value distribution.

Contribution

It introduces a novel compact-range measurement approach for small drone RCS at two frequencies and applies AIC for effective RCS data modeling.

Findings

RCS varies with frequency and direction.

RCS at 25 GHz exceeds that at 15 GHz.

GEV distribution effectively models RCS data.

Abstract

The knowledge of the radar signature of aerial targets, such as drones, is critical in designing an effective radar detection system. It is a challenging task to measure the radar cross-section (RCS) of small drones. This paper describes a compact-range approach for measuring the RCS of small drones at 15 GHz and 25 GHz. The measurement results show that the average RCS of the three small drones varies with the radar frequency with higher reflections observed around certain directions. Moreover, the results show that for each drone, the RCS at 25 GHz is higher than the RCS at 15 GHz. Besides, information-theoretical based model selection for the RCS data is carried using the Akaike information criterion (AIC). We find that the generalized extreme value distribution is a good fit for modeling the RCS of small drones.