Distortion-tolerant minimum-mean-squared-error filter for detecting noisy targets in environmental degradation

single-template algorithms are useful when the orientation of the target is known. However, if a target's exact aspect angle is unknown a priori, then multiple templates may be combined to yield a distortion- tolerant filter. In addition, the presence of environmental degradation between the target and the observer degrades the detection and classification performance of electro-optical sensors. We introduce a minimum- mean-squared-error filtering algorithm that takes into account the environmental degradation, additive system noise, nonoverlapping background noise, and target distortions. This distortion-tolerant filter is shown to be tolerant of different target aspects, and detects true class targets well in complex scenes.