New class separability measure for radar signals

Abstract

We propose a novel class separability measure for radar signals. To evaluate the discriminatory power of the radar signals, the proposed method first either calculates the correlation coefficients between two radar cross sections (RCSs), linearly shifts one-dimensional (1-D) high-resolution-range profiles (HRRPs), or rotates two 2-D inverse synthetic aperture radar (ISAR) images. Then, it uses the correlation coefficient when the two radar signals are best aligned. Next, the proposed method obtains new correlation- based discriminant matrices (CDMs) using the correlation coefficients. The mean value of the CDMs precisely represents the discriminatory power of the radar signal. Our experimental results show that the proposed method can accurately measure target separability.