XCS for Fusing Multi-Spectral Data in Automatic Target Recognition

We present our most recent efforts in applying XCS to automatic target recognition (ATR). We place particular emphasis on ATR as a series of linked problems, which include pre-processing of multi-spectral data, detection of objects (in this case, vehicles) in that data, and identification (classification) of those objects. Multi-spectral data contains visual imagery, and additional imagery from several infrared spectral bands. The performance of XCS, with robust features, notably exceeds that of a template-based classifier on the pre-processed multi-spectral data for vehicle identification. Promising preliminary results are also presented for vehicle detection. Future directions for this research are discussed in the conclusions.