Statistical Analysis of 1-D HRR Target Features

摘要

Automatic target recognitioin (ATR) and feature-aided trcing (FAT) algorithms that use one-dimensional (1-D) high range resolution (HRR) profiles require unique or distinguishable target features. This paper explores the use of statistical measures to quantify the separability and stability of ground target features found in HRR profiles. Measures of stability, ssuch as the mean and variance, can be used to determine the stability o f a target feature as a function of the target aspect and elevation angle. Statistical measures of feature predictability and spearability, such as the Fisher and Bhattacharyya measures, demonstrate the capability to adequately proedict the desired target feature over a specified aspect angular region. These statistical measures for separability and s tability are explained in detail and their usefulness is demonstrated with measured HRR data.