Naval air assets use a wide range of sensor modalities to detect and identify potential targets. While significant automated target recognition (ATR) packages have been researched for individual sensor modalities, no single ATR method exists to extract information from all of these disparate data sources. Cybernet is leveraging our existing orientation invariant ATR technique previously developed for use with EO/IR data for the Navy to develop a new ATR system for use with all data types. This technique combines the power of modern computer graphics with standard ATR concepts to create a very flexible recognition and classification system. Common ATR systems are designed for a specific type of sensor data. Our ATR solution works across sensor data types and can be expanded to include new sensor types as they are developed. Furthermore, the concept is capable of dealing with shadows and occlusions that typically produce errors in other ATR techniques.