Abstract:

To cope with the out-of-database target rejection problem in radar automatic target recognition (ATR), a method that artificially generates out-of-database examples and a weighted k nearest neighbors (KNN) classifier are proposed. By artificially generating out-of-database highresolution range profiles (HRRPs), the problem of acquiring out-of-database examples during the training step is solved. The weighted KNN classifier is both problem-dependent and data-dependent, and thus it is well suited for the associated rejection problem. Experiments conducted under the receiver operating characteristic (ROC) rule and the loss function rule respectively show that the weighted KNN classifier obtains satisfactory rejection ability.