Automatic Target Recognition: The Problems of Data Separability and Decision Making

This paper treats the problem of target recognition as a decision process. The nature of the decision to be made has a bearing on the data gathered and the subsequent processing. A key factor in the processing is the separability, i.e., the ability to distinguish, of radar images of similar but distinct objects. A number of recognition algorithms are considered and their suitability for data sets of various types is discussed. In addition some simple measurements of the transfer functions of two targets are considered. Observation suggest that the examples have characteristics that may make them readily separable. As with all recognition techniques the quality and quantity of training data available will place a limit on the performance of any recognition technique and this discussed in the text. The view is formed that a single technique is unlikely to be successful and several techniques cued by gross-features of the image may be more appropriate