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Discrimination of closely spaced objects using infrared sensors

This study uses simulated data from a set of two-band sensors and a set of three-band sensors. There are dozens of warheads and numerous decoys simulated (several decoys for each warhead). For a large part of the scenario, the objects are so close that individual targets cannot be resolved by the sensors, even though a single object's infrared signature could readily be detected. In those cases, multiple objects are seen as a single object, with the summed intensity of several objects. A BODE discrimination technique, which fits a quadratic and a sinusoid to the infrared time histories, is used to attempt to distinguish the warheads from the decoys. The average coefficients of the curve fit, along with their covariances, are used as features which describe the two object sets (warheads and decoys). Warheads and decoys can be readily distinguished once objects are far enough apart so that no multiple objects are mistaken as single objects. But when a cluster of objects appears as one object on the sensor focal plane, it is apparently impossible to tell whether or not a warhead is present in the cluster.