Application of Characteristic Function Method in Target Detection

Target detection is one of the important elements of Automatic Target Recognition (ATR) systems. In this paper, we propose a new approach to detect outliers in radar returns, based on modelling the background using an empirical distribution rather than a parametric distribution. The key innovation lies in the use of the Characteristic Function (CF) to describe the distribution. The experimental results show a promising performance improvement in terms of detection rate and lower false alarm rate, compared with the conventional Gaussian model which employs the Mahalanobis metric as a distance function.