A novel aspect independent resonance based radar target discrimination method has been developed in a previous work, and is found to be effective in discriminating canonical shape closely resembling objects with minor structural variations. The method utilizes the Radar Cross Section (RCS) of the unknown target to be identified and the distinction polynomial stored in the database (built from the dominant resonances of the known target). In this paper, the method is implemented successfully to discriminate two real size F5 aircraft with minor structural variations between them. This study involving real size targets poses some challenges that are overcome in this paper. The foremost challenge is the accurate computation of resonance range RCS of electrically large sized target considered (> 10λ), which is computationally demanding. The second challenge is in selecting the dominant resonances (features) of the complex target, useful for discrimination, from a large set of resonances representing the target. The accuracy of the discrimination result is dictated by the accuracy with which the features of the targets are identified. This in turn is dependent on the accuracy with which RCS is determined. To achieve accurate results, the exact Computational Electromagnetic (CEM) method - the Method of Moments (MoM) is used for computing the RCS of real size aircraft. The procedure to choose an optimal number of dominant natural resonant frequencies (NRFs) from a pool of NRFs for real size complex target is presented in this paper. The discrimination quantifying function `Risk' is shown to be effective in discriminating F5 aircraft - with and without missile attached underneath. The two targets have been successfully discriminated at all aspects, which is yet another challenge, establishing the aspect independent discrimination capability of the technique.
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