Surveillance sensors must operate in a signal environment which is dominated by clutter sources. These sources range from clouds, sun glint and terrain features to manmade objects such as smoke stacks, furnaces and other industrial representations. The task of an infrared surveillance sensor is to distinguish automatically objects of interest (targets) within the clutter. These targets may vary from aircraft and missiles to armored vehicles. Processing methods for clutter rejection have ranged from various thresholding techniques to spatial extent criteria to spectral discrimination. Temporal discrimination involves multiple pulse processing requiring successive looks at the scene. Spatial discrimination includes electrical filtering and measurement of signal characteristics in the focal plane of the sensor. Spectral discrimination utilizes the signature characteristics of targets and clutter to recognize their uniqueness. For best results all of these discriminants are collectively applied to the surveillance sensor's output through various techniques to filter out and reject the clutter-induced signals.