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Examinando (Espacio) Artículos por Materia "Actual measurements"
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Publicación Acceso Abierto Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles(Multidisciplinary Digital Publishing Institute (MDPI), 2015-01-05) López Rodríguez, P.; Escot Bocanegra, D.; Fernández Recio, R.; Bravo, I.; Instituto Nacional de Técnica Aeroespacial (INTA); Agencia Estatal de Investigación (AEI)Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising.Publicación Acceso Abierto Singular Value Decomposition Applied to Automatic Target Recognition with High Resolution Range Profiles(Multidisciplinary Digital Publishing Institute (MDPI), 2014-01-02) López Rodríguez, P.; Escot Bocanegra, D.; Fernández Recio, R.; Bravo, I.; Instituto Nacional de Técnica Aeroespacial (INTA)Abstract: With the development of wideband radars new applications have emerged related to this kind of sensor. That is the case of automatic target recognition based on radar imagery. In this paper a target recognition methodology based on one dimensional high resolution radar imagery is presented. 1D radar images, namely high resolution range profiles (HRRP) are comprised of range bins and contain the distribution of the scattering centers of a target providing information about target structure. In this manuscript, identification of HRRP coming from measurements of in-flight aircraft is carried out by comparison with a database of simulated HRRPs. Simulated HRRPs have a very clean signature while actual HRRPs suffer from noise and other unwanted effects making the recognition process an arduous task. In order to overcome the differences between profiles, Singular Value Decomposition (SVD) is applied to matrices of HRRP. SVD is a robust tool for the decomposition of any matrix into orthogonal basis spaces, thus, by applying SVD to the HRRP matrices and selecting the most significant singular vectors, the matrices can be split into a signal and a noise subspace. The identification algorithm proposed in this paper is based on finding the aircraft which minimizes the angle between signal subspaces. Confusion matrices for the classification of the whole test set and error rates obtained will be provided in the paper full-version. As will be shown, the use of SVD provides good recognition rates even the lack of similarity between actual and simulated profiles.
