The recent public release of high resolution Synthetic Aperture Radar (SAR) data collected by the DARPA/AFRL Moving and Stationary Target Acquisition and Recognition (MSTAR) program has provided a unique opportunity to promote and assess progress in SAR ATR algorithm development. This paper will suggest general principles to follow and report on a specific ATR performance experiment using these principles and this data. The principles and experiments are motivated by AFRL experience with the evaluation ofthe MSTAR ATR.

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A n important issue in developing a Model-Based Vision approach is the specification of features that are -(a) invariant t o viewing and scene conditions, and also -(b) specific, i.e., the feature must have different values for different classes of objects. We formulate a new approach for establishing invariant features.Our approach considers not just surface reflection and surface geometry, but it also takes into account internal object composition and state which affect images sensed in the non-visible spectrum. This new type of invariance is called Thermophysical Invariance. The approach is based on a physics-based model that is derived from the principle of the conservation of energy applied at the surface of the imaged object.

An important issue in developing a model-based vision system is the speci cation of features that are-(a) invariant to viewing and scene conditions, and also-(b) speci c, i.e., the feature must have di erent values for di erent classes of objects. We formulate a new approach for establishing invariant features. Our approach is unique in the eld since it considers not just surface re ection and surface geometry in the speci cation of invariant features, but it also takes into account internal object composition and state which a ect images sensed in the non-visible spectrum. A new type of invariance called Thermophysical Invariance is de ned. Features are de ned such that they are functions of only the thermophysical properties of the imaged objects. The approach is based on a physics-based model that is derived from the principle of the conservation of energy applied at the surface of the imaged object.