Multi-Aspect Data Fusion Applied to Electromagnetic Target Classification using Enetic Algorithm

Abstract

Electromagnetic target detection and classification is an important problem relevant not only to military applications but also to civilian use. In the problem of a breast tumor detection and identification [1], for instance, the main concern is accuracy. In the case of the recognition of a military target such as an aircraft or a ship, on the other hand, speed of classification is as important as the accuracy of the decision as such a decision should be made within a fraction of a second. For the K-pulse target identification technique used in this research, the K-pulse design phase is rather complicated and time consuming but the interactive decision process, that is the only phase of identification to be completed in real-time, is very simple and fast.