Passive Optical (Visible-LWIR) Signatures
Since 1974, TBE scientists and engineers have been responsible for maintaining, enhancing, and applying optical signature models and data for missile defense. We develop industry standard M&S tools, such as the Optical Signatures Code (OSC) and OPTIcal Signature In-line Generator (OPTISIG), and continue to enhance and expand the capabilities of our tools. OSC is a flexible and powerful tool for computing signatures of missiles, missile payloads, countermeasures, and associated objects, and OPTISIG is the fast-running counterpart to OSC.
We also contribute to the development of integrated scene tools such as the Synthetic Scene Generation Model (SSGM) and Fast Line-of-sight Imagery for Target and Exhaust-plume Signatures (FLITES). SSGM hosts OSC and OPTISIG, along with a suite of background/clutter models. TBE provides the OSC-to-FLITES interface as a means of injecting high-fidelity target/threat data into FLITES, which is the new MDA standard for integrated scene generation.
Our M&S capabilities are complemented by an in-house spectroscopy laboratory, where we can make high-resolution measurements of UV, visible, and IR reflection and transmission characteristics of material specimens.
Active (Radar and Ladar) Signatures
We use government standard tools (such as the Xpatch suite) to predict radar cross section (RCS), range profiles, and laser radar (ladar) cross sections of objects pertinent to missile defense. Our analysts have studied RCS data from fixed, land-mobile, and shipboard radar systems, and they assist in the planning and conduct of flight tests and radar range/chamber experiments to characterize targets.
Statistical Pattern Recognition and Automatic Target Recognition
We employ techniques of statistical pattern recognition and automatic target recognition, collectively called discrimination, in missile defense applications. TBE analysts have studied the effectiveness of discrimination algorithms, penetration aid designs, and defense architectures, and we perform end-to-end analysis by developing algorithms, selecting statistical features, and evaluating the performance of systems.
We have demonstrated the use of pattern recognition in diverse fields, including explosive detection and typing (e.g., IED mitigation) and industrial radiographic inspection. We pioneered the use of genetic algorithms (evolutionary computing) to solve non-linear, inverse problems in target design, data analysis, and intelligence applications.
Our hardbody and plume modeling process covers all phases of the threat timeline, from launch to impact of SRBM, MRBM, IRBM, and ICBM/SLBM class threats. TBE develops high-fidelity models based on intelligence information and engineering studies. Our tools and methods support efficient calculation of spectra and in-band signatures for numerous wavelengths and lines of sight. We have delivered terabytes of documented data to support algorithm design/development, systems engineering, digital simulations, and HWIL systems.