The U.S. Navy has been requested to provide insightful responses to questions regarding low and high resolution target discrimination and target classification capabilities for short medium range ballistic missiles (SRBM/MRBM). Specific targets studied for this paper include foreign solid booster exhaust plume and hardbody systems (PHS). Target gradient edge intensities were extracted for aimpoint selection and will be added to the pattern referencing library database at NSWC Dahlgren Division. The results of this study indicate an increasing requirement for advanced image processing on the focal plane array of a LEAP (light exoatmospheric projectile) type kill kinetic vehicle (KKV) in order to implement effective correlation matching routines.
The U.S. Navy has been requested to provide insightful responses to questions regarding low and high resolution target discrimination and target classification capabilities for short and medium range ballistic missiles (SRBM/MRBM). Specific targets studied for this paper include the solid booster and the associated attitude control system (ACS) liquid divert thruster systems. Discriminants selected include booster and ACS separation debris, as well as fuel vent phenomena. Debris and vent cloud containment and elimination through Gaussian suppression techniques have been implemented for low resolution assessment for target detection and tracking. Target gradient edge intensities were extracted for aimpoint selection and will be added to the pattern referencing library database at NSWC. The results of this study indicate an increasing requirement for advanced image processing on the focal plane array of a generic LEAP (light exo-atmospheric projectile) type kill kinetic vehicle (KKV) in order to implement effective target and aimpoint detection/tracking correlation matching routines.
(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.
One of the primary inhibitory factors for resolution of automatic target recognition (ATR) performance problems has been the inability to quantitatively characterize low signal-to-noise (SNR) target detection and classification algorithms, especially those which are challenged by high spatial frequency backgrounds. The preceding work addressed obtaining classification statistics and geometric pattern referencing characteristics with the target mean intensity distribution commensurate with the background intensities. The current effort maintains a similar approach; however, the ratio of target-to-background intensity is significantly reduced. This is achieved by increasing the obscurant's ratio of differential scattering cross section-to- total cross section (albedo). The objective is to establish 50 percent of the edgels (target edge pixels) on the target at maximum sensor-to-target range in the presence of high spatial background frequencies, including obscurants. In addition precipitation rate and range, as well as variation in obscurant albedo, are assessed. Since scenario dynamics is sought, no attempt is made to resolve target edgels as a function of a single variable, for example precipitation. All variables are allowed to vary independently. The synthetic smoke generated for these plates incorporates the combat obscuration model for battlefield induced contaminants (COMBIC). The target and background imagery is taken in the LWIR by a Keewenaw Research Center (KRC) TMI FLIR. The final images are morphologically processed, segmented, high SNR scenes. The findings are that the target set need not be of a higher intensity than the surrounding imagery, as required in many matched filter operations; the target need only possess a higher intensity gradient than the background clutter and obscurants. Smoke and obscurant intensities may be significantly reduced, or even removed, by this type of morphological image processing.
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