Denoising With Inherent Scattering Characteristic for 2-D Radar Cross Section Measurement

Abstract

Noises from the measurement sensors are inevitable in radar cross section testing due to the thermal agitation of electrons in imperfect conductors. Existing methods represented by wavelet threshold usually regard the measured data as a stationary stochastic signal, ignoring the inherent influence of the target under test, which inevitably removes the signal’s component when noise increases. This paper proposes a novel perspective on 2-D radar cross section measurement denoising, considering the target’s inherent scattering characteristics (ISC). In the proposed method, the noise and the target are firstly separated as far as possible in the generalized Fourier series domain while the target’s component is all preserved. Then, the noise is further suppressed by the scattered field reconstruction of the Hankel function. Finally, a metal sphere being a calibrator is introduced to improve the denoising ability. Both simulations and experimental studies demonstrate the superiority of our method compared with existing algorithms. Results indicate that the proposed method can achieve higher accuracy.