OUSD (R&E) MODERNIZATION PRIORITY: Artificial Intelligence/Machine Learning, Hypersonics TECHNOLOGY AREA(S): Battlespace, Information Systems The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws. OBJECTIVE: Identify and develop techniques to analytically correlate and efficiently represent geometric perturbations with millimeter wave target scattering for use in existing scene generation application DESCRIPTION: The U.S. Army employs a wide array of radar simulations to include all-digital, signal injection, and hardware-in-the-loop environments to conduct high fidelity, cost effective, millimeter wave (MMW) weapon system development and evaluation. These simulation environments are used in sensor and seeker performance assessments, flight test analysis, and algorithm developments and are driven by high-fidelity target and threat radar scattering models which are validated against available referent signatures. MMW target signatures may be derived from a variety of physics based, signature prediction tools that utilize computer aided design (CAD) geometry models as inputs. CAD inputs are routinely modeled as pristine geometry sources as a philosophical choice to avoid exact fingerprinting of a single target instance in addition to real-world limitations such as a lack of input information, memory limits, or polygon budgets. That said, real-world target structures may exhibit a wide range of non-pristine geometric surfaces and unit-to-unit variability due to operational use, battle and test damage, manufacturing processes, and fabrication tolerances. For millimeter wave applications, geometry perturbations can produce significant deviations in radar scattering parameters to include dominant scattering amplitude, physical location of scattering, as well as the angular extent of scattering phenomenology as experienced for ground and air targets. While existing radar target models provide high fidelity inputs to scene generator applications, radar inputs to scene generation are generally not correlated to or functionally representative of underlying perturbations in target geometry and are handled on a discrete basis. In addition, a significant development resources are expended in MMW radar signature model creation and validation to discern and account for effects of non-pristine geometry elements that may be modeled by polygonal, spline, or parametric solid entities. Previous research has approached target variability through statistical variation of observed target signatures. While statistical variability methodologies present valuable approaches for modeling signature variation over a target class, the current desire is to research and address the correlation of geometric perturbations and radar signature modeling at the source CAD and scattering physics level. Techniques are required to analytically correlate and functionally represent target geometric perturbations in millimeter wave radar models for use in existing scene generation applications and simulation environments to include the Army's Common Scene Generator (CSG), CCDC AvMC hardware-in-the-loop (HWIL) facilities, and CCDC AvMC Virtual Target Center (VTC) predictive models. This would allow modeling flexibility and ensure simulation environments are driven by millimeter wave models that capture and quantify the effect of geometry perturbations encountered with a target structure while reducing development duration and validation complexity. The modeling approach for this effort should be adaptable for integration to radar signal generation chains within existing simulations with emphasis on Ka-band scattering for both ground and air assets. Considered solutions should be capable of application to any desired physics-based radar predictive signature application with further extension to empirically derived, measurement-based target modeling. In addition, techniques and methodologies should support VTC validation processes with comparison to empirical data sets. PHASE I: Identify an approach and demonstrate a methodology to support the analytical correlation of target CAD geometry and associated geometric perturbations to Ka-band scattering from air and ground targets. Quantify implementation and interface requirements for existing CAD modeling, predictive signature, and scene generator applications based on proof-of-concept approaches. Research and recommend methods for metric assessment of model enhancements accounting for perturbation effects as applied to the virtual target validation process. PHASE II: Develop corresponding algorithms, processes, and frameworks to support assessment, test, execution, and demonstration of correlated CAD geometry and radar scattering model perturbation approaches. Finalize a software toolkit for target model creation and development with demonstrated support of the Virtual Targets Center validation process for a sample high fidelity ground target geometry. Address implementation requirements with CAD, predictive radar, and scene generation applications. PHASE III DUAL USE APPLICATIONS: Integrate correlated perturbation techniques and software application into validation processes used by the Army Virtual Targets Center for support of target model generation for all-digital and HWIL simulation environments. Conduct an end-to-end creation, correlation, and perturbation refinement an air and ground target system at Ka-band. Conduct formal validation of final target model results through the virtual target validation process. REFERENCES: J.A. Sokolowski and C.M. Banks, editors, Modeling and Simulation Fundamentals: Theoretical Underpinnings and Practical Domains. Hoboken, NJ, John Wiley & Sons, 2010. William E. Nixon, H. J. Neilson, G. N. Szatkowski, Robert H. Giles, William T. Kersey, L. C. Perkins, Jerry Waldman, "Variability study of Ka-band HRR polarimetric signatures on 11 T-72 tanks", Proc. SPIE Vol. 3370, p. 369-382, Algorithms for Synthetic Aperture Radar Imagery V Edmund G. Zelnio; Ed. September 1998; [3] Stephanie Brown Reitmeier, Missile Simulation in Support of Research, Development, Test Evaluation and Acquisition, National Defense Industrial Association (NDIA), 15 May 2012. https://modelexchange.army.mil. KEYWORDS: computer aided design, CAD, radar cross section, Ka-band target modeling, geometric correlation, radar scattering, signature prediction
