TECHNOLOGY AREAS: Air Platform, Information Systems, Sensors, Battlespace

ACQUISITION PROGRAM: PMA-290, Maritime Patrol and Reconnaissance Aircraft

OBJECTIVE: Develop computational electromagnetics (CEM) tools to analyze and optimize on-aircraft antenna/radome performance.

DESCRIPTION: Antennas used on Navy aircraft are either commercial off the shelf (COTS) or are designed in free space, i.e., there are no objects nearby to disturb their performance. Installation of an antenna on a platform may alter its properties significantly. Develop CEM tools that will assess this change in properties and that will perturb the design of an antenna and its radome in an effort to restore the original (desirable) properties.

Aircraft radome design is a balance between electrical, aerodynamic and structural performance. Radome electrical performance is quantified in terms of transmission efficiency, antenna pattern degradation, boresight error and relative cross polarization level. While radome wall insertion loss is typically held to small values, in many instances it is the scattering loss off the internal structures that dominates the overall performance. The scattered energy spreads out into the antenna side lobes corrupting the antenna pattern. The objective of this effort is to use an exact-physics CEM code to achieve accuracy comparable to that from a high-quality antenna measurement range. Radome related parameters of interest to be computed with this code include transmission loss, beam deflection (boresight error), its rate of change with antenna scan, antenna pattern distortion, monopulse null depth degradation (as applicable) and cross polarization levels. Accuracy of +/- 0.1 dB in gain and +/- 3 degrees in phase over the peak 10 dB of element or array pattern is needed for the combined radome and antenna model. Due to the size of the problem, such a code should be able to run efficiently on central processing unit (CPU) and CPU/graphics processing unit (GPU) clusters. In case the antenna strongly interacts with a major part of the airframe, a hybrid code, comprising an exact-physics code for the antenna and its immediate surroundings and a high-frequency code for the rest of the platform, is desirable.

The second step involves the restoration of one or more of the antenna's properties. An optimization code is needed that is well integrated with the CEM analysis code. This code should use as few computational points as possible. Multi-dimensional interpolatory methods may be used toward this end. The objective should be to satisfy certain requirements (e.g., antenna gain greater than X dB, sidelobe level below Y dB, etc.) rather than search for locally or globally optimal points. The independent variables in the optimization scheme should be the antenna and radome dimensions and material properties, as installed on the aircraft and subject to aerodynamic and structural constraints. The code should run efficiently on CPU and CPU/GPU clusters.

The result of this effort should be an antenna/radome analysis and design tool that can be used for a wide range of installed antenna problems with a high degree of confidence. A well designed graphical user interface (GUI) should guide the user through the process of engaging the code. Teaming between CEM and optimization experts is encouraged.

PHASE I: Demonstrate capabilities of one or more CEM and optimization codes. Choose the most promising CEM and optimization code. Perform further analysis/ computation to assess the developmental stage of the two codes. Develop a detailed outline of the requirements and plan what would be accomplished in Phase II.

PHASE II: Execute the requirements program developed in Phase I. Integrate CEM and optimization codes. Port codes on clusters of CPUs and CPU/GPUs. Test and demonstrate the resulting codes on cases of interest to NAVAIR. Design and develop the GUI.

PHASE III: Refine methodology and tool developed either alone or in partnership with another company and transition to interested platforms.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: The technology developed under this topic has direct utility in a wide variety of commercial and military applications, such as radar, communications and navigation.

REFERENCES:
1. Kolundzija, B. M., & Djordjevic, A. R. (2002). Electromagnetic Modeling of Composite Metallic and Dielectric Structures. Artech House.

2. Taflove , A. & Hagness, S. C. (2005) . Computational Electrodynamics: The Finite-Difference Time-Domain Method, 3rd Edition. Artech House.

3. Jin, J. (2002), The Finite Element Method in Electromagnetics, John Wiley & Sons, Inc.

4. Cockburn, B., Karniadakis, G. & Shu, C.-W. (Eds.) (2000) Discontinuous Galerkin Methods: Theory, Computation, and Applications. Lecture Notes in Computational Science and Engineering. Springer-Verlag.

5. Moré, J. J. & Wright, S. J. (1987). Optimization Software Guide. SIAM.

6. Steuer, R.E. (1986). Multiple Criteria Optimization: Theory, Computations, and Application. John Wiley & Sons.

7. Goudos, S. K. & Sahalos, J. N. (2010). Pareto Optimal Microwave Filter Design Using Multiobjective Differential Evolution, IEEE Trans Antennas Propagat.

8. Miller, E.K., (1998). Model-based parameter estimation in electromagnetics: Part III, Application to EM integral equations, IEEE Antennas Propagat Mag.

KEYWORDS: Computational electromagnetics; antennas; radomes; modeling and simulation; optimization; CPU/GPU clusters

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