Relative performance of correlation-based and feature-based classifiers of aircraft using radar range profiles

A surveillance system which automatically classifies aircraft can be very useful, especially with the problem of congestion at large airports. This paper evaluates the performance of correlation- and feature-based classifiers on a set of four simulated radar targets over a wide range of target orientations. Experiments are performed for a range of radar bandwidths in order to determine the effect of radar bandwidth on the relative classification performance. Only 1D radar range profiles are considered since it is assumed that the aircraft are classified using few profiles and the orientation of the aircraft in each profile is known only approximately. The results suggest that feature-based classifiers outperform correlation-based classifiers and that classification performance is highly dependent on the orientation of the aircraft, but that accurate classification of approaching aircraft is possible