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Title: Multi-perspective radar target classification
Author: Vespe, Michele
ISNI:       0000 0004 2672 3178
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2007
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The problem of radar target classification is examined for the case when more than one per spective or viewing angle of the target is available to the sensor. It is shown how multiple perspectives enhance the classification performance through the analysis of the classification results on full scale target signature measurements. Furthermore, the classifier capabilities are explored as a function of the number of perspectives, the angular perspective displacements, the signal to noise ratio, the resolution and the illuminating wavelength. In order to remove any possible bias that could be introduced by a single individual classifier, various approaches to Multi-Perspective (M-P) classification have been implemented, using both High Range Res olution (HRR) profiles and 2-D images from real Synthetic Aperture Radar (SAR) and Inverse SAR (ISAR) data. The classification performance is also described for those applications where the perspective displacement information is known and can be processed. The results show a consistent improvement in classification performance as the number of perspectives increases. The techniques employed also provide considerable insight into the classification process highlighting the degree of complexity of this extremely challenging problem.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available