A comparison of 1D and 2D algorithms for radar target classification

Abstract

The use of high-resolution radar measurement data (35 GHz) from four ground vehicles (bulldozer, Dodge Power Wagon, Dodge Van, and Camaro) to evaluate the performance of several 1D and 2D classifiers is discussed. The 1D classifiers use high-resolution range profiles to classify targets; the 2D classifier uses high-resolution inverse synthetic aperture radar (ISAR) images to classify targets. Classification performance results using the 1D and 2D algorithms are presented, and it is shown that the 2D algorithm performed best.<>