The emergence of multi-band sensor technology, e.g. in the thermal infrared, promises significant improvements in TA (Target Acquisition) performance. With these new sensor systems, targets may be distinguished from their background not only on the basis of differences in radiation magnitude in the sensor's spectral range (as is the case with single-band systems), but also on differences in spectral properties. However, existing end-to-end sensor performance measures, such as the MRTD, MTDP and TOD laboratory tests or the NVTherm model, produce threshold curves of resolution vs. thermal or luminance contrast and do not take spectral difference into account. Until now no test methodology exists to characterize or quantify the additional benefits of a multi-band sensor above a single-band system. We propose an extension to the current end-to-end test methods that may overcome this shortcoming. The method yields a 2-D threshold surface of resolution, contrast and spectral difference between a test pattern and its background. This surface may be used in TA models to predict the ability of a human observer, using the sensor system, to recognize or identify a target given its size, radiance difference and spectral difference with the background. The extension can be incorporated in the TOD, but in other sensor performance measures as well.