High-Dimensional Range Profile Geometrical Visualization and Performance Estimation of Radar Target Classification via a Gaussian Mixture Model

In this paper, a method of data visualization and classification performance estimation applied to target classification is proposed. The objective of this paper is to propose a mathematical tool for data characterization. The principle is to use a non linear dimensionality reduction technique to describe our data in a low-dimensional space and to model embedding data by Gaussian mixture model (GMM) to estimate classification performance graphically and analytically.