MULTI-ASPECT DATA FUSION APPLIED TO ELECTROMAGNETIC TARGET CLASSIFICATION USING ENETIC ALGORITHM

摘要

For the first time in literature, use of multi-aspect data fusion in the Genetic Algorithm-based K-pulse design problem (i.e. in the passive phase of the proposed target classification process) is formulated and successfully demonstrated for spherical dielectric targets. Target classification tests for two spherical targets with the same size but different refractive indices have resulted consistently correct at all test cases, including the aspects which were not previously used in the K-pulse design process. As a future work, use of decision fusion at the real-time (active) classification phase will be studied to further improve the overall performance of the K-pulse target classification technique.