Government-sponsored blind tests have demonstrated that the applied analysis spectral analytical process (AASAP) is highly robust and efficient in its ability to detect sub-pixel targets in strongly cluttered backgrounds. Multispectral signals or data are processed by AASAP to search for specified targets on a pixel-by-pixel (or IFOV-by-IFOV) basis. Targets are acquired and typed based on their spectral signature alone, and the targets can occupy small fractions of mixed pixels. No scene knowledge other than the signature of the target is needed. The signatures can be derived either empirically using the sensor, or they can be modeled using laboratory or field spectral measurements. Signals or data are processed using an intelligent background removal process, and the residuals are processed to extract the signature. The extracted signatures are compared to a library of one or more reference target signatures to determine whether or not a target is present and to type it. Sponsored tests have revealed that low-spectral-contrast targets occupying as little as 15% of an IFOV (or mixed pixel) can be reliably detected with low false alarm rates using five or more spectral bands. Tests demonstrated robustness in highly cluttered and variable backgrounds and variable atmospheric conditions. AASAP is an automated process, and its efficiency and architecture are supportive of potential on-board implementations.