An Improvement of Kulemin Models for FOD Detection

Abstract

Foreign Object Debris (FOD) has severely injured airport or airline personnel or damaged equipment in airports. However, echoes from runway and lawn are much stronger than that from FOD. Thus efficient detection methods are based on the reasonable clutter model and precise scattering coefficient. This paper improves Kulemin models to describe the backscatter coefficients more exactly. First of all, the runway and lawn are divided into scattering cells. Employing Ulaby’s test data of these two terrains, we modify Kulemin models by Least Square (LS) fitting. Simulations show that if CNR=-20dB, the mean square errors (MSE) of runway and lawn models are both less than -38dB when the grazing angle is increasing from 0.5647° to 2.9647° , which conforms to the actual situation of FOD detection in airport.