Robustness of automatic target recognition (ATR) to varying observation conditions and countermeasures is substantially increased by use of multispectral sensors. Assessment of such ATR systems is performed by captive flight tests and simulations (HWIL or complete modeling). Although the clutter components of a scene can be generated with specified statistics, clutter maps directly obtained from measurement are required for validation of a simulation. In addition, urban scenes have non-stationary characteristics and are difficult to simulate. The present paper describes a scanner, data acquisition and processing system used for the generation of realistic clutter maps incorporating infrared, passive and active millimeter wave channels. The sensors are mounted on a helicopter with coincident line-of-sight, enabling us to measure consistent clutter signatures under varying observation conditions. Position and attitude data from GPS and an inertial measurement unit, respectively, are used to geometrically correct the raw scanner data. After sensor calibration the original voltage signals are converted to physical units, i.e. temperatures and reflectivities, describing the clutter independently of the scanning sensor, thus allowing us the use of the clutter maps in tests of a priori unknown multispectral sensors. The data correction procedures are described and results are presented.