Singular Value Decomposition Applied to Non-Cooperative Target Identification

Abstract

One of the main concerns in the Security and Defense area is to identify quickly and reliably different in-flight targets, especially in hostile scenarios. A non-cooperative classification system could identify targets at long range and under conditions of poor visibility without requiring aircraft collaboration. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on feature extraction techniques applied to High Resolution Range Profiles is presented. The identification methodology is conducted by comparison of a collection of range profiles of a unknown target, namely test set, with a pre-loaded database of known potential signatures, namely training set. In order to evaluate the performance of the presented algorithms, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement campaign. The most evident issue of using synthetic signatures instead of measured profiles is that simulated profiles implies an ideal recognition scheme, since datasets have the same high quality. So as to confirm the validity of the approach, additive white Gaussian noise has been considered to the profiles in the test set.