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Predict Antenna Coupling on Electrically Large Platforms Before Building Hardware

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Why This Matters

This white paper highlights a significant advancement in predicting antenna coupling on large platforms, enabling designers to accurately assess energy leakage before hardware implementation. This capability is crucial for optimizing the performance and safety of complex radio systems on aircraft, ships, and vehicles, reducing costly trial-and-error testing. The innovative simulation approach addresses longstanding challenges in modeling large, electrically complex structures with low-level coupling signals, offering a valuable tool for the tech industry and consumers alike.

Key Takeaways

IEEE Spectrum and Wiley are proud to bring you this white paper, sponsored by WIPL‑D.

More Information

Aircraft, ships and vehicles now carry many radio systems in a small space, so designers must know how much energy leaks from one antenna into another before any hardware is built. This leakage is described by the mutual s-parameters between the antenna ports, and it decides whether two systems can operate at the same time on the same platform. Measuring it by trial and error at every candidate position is slow and costly. Predicting it by simulation is difficult for two reasons. First, the platform is electrically large, which means that its dimensions span several hundreds of wavelengths, so the model needs a large number of unknowns. Second, the coupling levels of interest are very low, in some cases down to -100 dB, which leaves little margin for numerical error. This White Paper addresses both problems with a full-wave solution based on the Method of Moments applied to the Surface Integral Equation, using higher-order basis functions to keep the number of unknowns low. Two examples are studied in detail: a metallic cube carrying two quarter-wavelength monopoles, and a realistic airliner carrying five monopoles at 1.06 GHz, where the fuselage is about 140 λ long. Three modelling techniques for obtaining accurate low-level results are compared in terms of accuracy and the number of unknowns each one requires, and the complete geometry of each model is documented so that every result can be checked independently.