Nonlinear Spectral Analysis of Radar Clutter

Abstract

<p>This thesis is concerned primarily with the spectral analysis of clutter in an air traffic control (ATC) radar environment, which is produced by such objects as weather disturbances and migrating flocks of birds. The aim is to provide a means for the on-line classification of the different forms of clutter in such an environment. With the clutter identified and displayed for the operator, aircraft can be vectored in a way to avoid hazardous areas. This separation and identification of radar echoes may also be useful in studies relating to meteorology and ornithology.</p> <p>Since the mechanisms which give rise to weather clutter and bird echoes are different, it is reasonable to expect that they have different statistical parameters. One of these parameters, spectral spread, provides a convenient measure for comparison. To perform the separation of clutter based on spectral spread, a high resolution method is necessary. In this thesis, the maximum entropy method (MEM) is applied to clutter classification. It is shown that the resolution and stability properties of the MEM are well-suited for the separation of different types of clutter; particularly weather from birds. The analysis is performed on both computer-simulated and actual clutter signals. In each case, the results are compared with those obtained by applying the Welch method of averaged modified periodograms. This comparison has revealed that the Welch method does not have the necessary resolution for the classification of clutter.</p>