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

2002-01-01
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.
Citation Formats
G. Sayan, Multi-Aspect Data Fusion Applied to Electromagnetic Target Classification using Enetic Algorithm. 2002, p. 539.