Since High Resolution Radar provides the ability to recognize targets at long distance and under any weather condition, Non-Cooperative Target Identification based on High Resolution Range Profiles has become a key research domain in the Defense industry. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on the exploitation of Singular Value Decomposition applied to a matrix of range profiles is presented. The method compares a collection of profiles of a given target, namely test set, with the profiles included in a database, namely training set. The classification is improved by using the decomposition, since it allows to model each aircraft as a subspace and to accomplish recognition in a transformed domain where the main features are easier to extract hence, reducing unwanted information. In order to evaluate the performance, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement campaign. Taking into account the nature of the datasets, the main drawback of using simulated profiles instead of actual measured profiles is that the former implies an ideal identification scenario, while measured profiles suffer from unsought information. So as to confirm the feasibility of the approach the addition of noise has been considered before the creation of the test set. Identification experiments of profiles are conducted for demonstrating which methodology provides the best robustness against noise in an actual possible scenario. Future experiments with larger sets are expected to be conducted with the aim of finally using actual profiles as test sets in a real hostile situation.