Classification of radar clutter in an air traffic control environment

The results of an experimental study aimed at the classification of radar clutter encountered on ground-based coherent scanning radar systems used for air traffic control are presented. The clutter signals of interest are primarily those due to birds and to clouds and weather systems. A historical perspective on the radar clutter classification problem is given, and related issues are discussed. The important features of radar as a sensor in an air traffic control environment are described, and physical phenomena in radar clutter and targets, which provide the physical basis for the discrimination between the different radar clutter classes, are discussed. The feature of selection/extraction procedure, which is based on the multisegment Burg algorithm, is described. The experimental evaluation of a parametric Bayes classifier and a neural network classifier is reported.<>