(U) Future successful ballistic missile booster intercepts will require advanced automatic target detection, tracking, classification and identification (ADTCI) image processing techniques. Two such techniques are presented in this classified SECRET paper using the synthetic scene generator model (SSGM) in combination with the advanced systems (AVS) image processing package. Two challenging multispectral cases are treated: (1) missile hardbody occultation by the missile exhaust plume, and (2) variable plume/hardbody system (PHS) gradient intensities generated by missile tumbling due to exiting the sensible atmosphere. The target detection, tracking and edge extraction methods selected for this study include morphological, open-close operations within decision- level fusion for the obscuration case and pixel-level fusion for variable edge intensities. Other investigators have approached this issue on similar image processing techniques. The multispectral (2.69 - 2.95 micrometer SWIR; 4.17 - 4.2, 4.35 - 4.50 micrometer MWIR; and 8.0 - 12.0 micrometer LWIR) target/background imagery includes SWIRM/MWIR boost phase track (with occlusion problem) and LWIR aimpoint selection (with tumbling problem). The two classified missile systems are: (1) a depressed-angle submarine launched ballistic missile (SLBM) and (2) a medium range ballistic missile (MRBM). The results indicate that for 6 degrees of freedom (6 DOF) hardbodies, ATDCI geometrical pattern reference libraries should be optimized to accommodate the extreme variable gradient geometries for tumbling midcourse targets. For boost- phase missile hardbody occultation by missile exhaust plumes, segmentation and feature extraction should be implemented in each bandpass before processing to the ATDCI classifier. This study demonstrates that although the plume/hardbody system edges were extracted, the geometry of the target edge often deviated from symmetry.