Optimized Artificial Impedance Surface Design
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Solution Overview
Problem
Existing methods for creating artificial impedance surfaces rely on assumed surface wave profiles, leading to suboptimal efficiency due to edge scattering and local impedance variations, resulting in less than optimal conversion of excitation input power to desired far field radiation patterns.
Innovation Solution
A method for determining an optimized artificial impedance surface by calculating actual surface wave profiles, using electromagnetic simulation tools to account for edge scattering and varying impedance boundary conditions, and iteratively recalculating the impedance pattern until a predetermined criterion is met, ensuring the desired far field radiation pattern is achieved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If an assumed surface wave profile is used to determine the impedance pattern, then the design process is simplified, but the efficiency of conversion from excitation input power to the desired far field radiation pattern deteriorates
Solution Approach 1:
The patent implements an iterative optimization process where the actual surface wave profile calculated from the impedance pattern is fed back to update the impedance pattern. This feedback loop continues until convergence, ensuring that the final impedance pattern accounts for edge scattering and local impedance variations, thereby maximizing conversion efficiency while maintaining manageable design complexity through automation.
Solution Approach 2:
The patent performs preliminary calculation of the actual surface wave profile using an electromagnetic simulation tool before finalizing the impedance pattern. This preliminary action identifies deviations from the assumed profile due to edge effects and local variations, allowing the design to be optimized in advance before manufacturing, thus improving efficiency without significantly increasing overall design complexity.
2Device complexity
If edge scattering effects and local impedance variations are ignored, then the design calculation is simpler, but the accuracy of the far field radiation pattern deteriorates
Solution Approach 1:
The iterative optimization process uses feedback from electromagnetic simulation to continuously refine the impedance pattern. Each iteration calculates the actual surface wave profile including edge scattering effects, compares it with the desired pattern, and updates the impedance values accordingly. This feedback mechanism ensures high radiation pattern accuracy while keeping calculation complexity manageable through automated convergence.
Solution Approach 2:
The patent systematically varies impedance parameters across the surface based on calculated optimal values that account for edge scattering and local variations. By changing impedance parameters iteratively rather than using a fixed assumed profile, the method achieves high radiation pattern accuracy. The electromagnetic simulation tool automatically handles the complex calculations, preventing excessive manual calculation complexity.
3Manufacturing precision
If an iterative optimization process is performed to account for actual surface wave profiles, then the far field radiation pattern accuracy is improved, but the calculation time and computational complexity increase
Solution Approach 1:
The iterative optimization process employs feedback from electromagnetic simulation to refine the impedance pattern progressively. The simulation tool automatically converges to an optimal solution within a finite number of iterations, balancing accuracy improvement with acceptable calculation time. The automated nature of the feedback loop eliminates manual intervention, reducing overall computational burden despite multiple iterations.
Solution Approach 2:
The patent uses electromagnetic simulation to create a virtual model of the impedance surface and its radiated fields. This computational copy allows for rapid iteration and optimization without physical prototyping. The simulation accurately replicates electromagnetic behavior including edge scattering effects, enabling high radiation pattern accuracy to be achieved through virtual testing and optimization rather than time-consuming physical trials.
Data Source
AI summary
A method and system for determining an optimized artificial impedance surface is disclosed. An artificial impedance pattern is calculated on an impedance surface using an optical holographic technique given an assumed surface wave profile and a desired far field radiation pattern. Then, an actual surface wave profile produced on the impedance surface from the artificial impedance pattern, and an actual far field radiation pattern produced by the actual surface wave profile are calculated. An optimized artificial impedance pattern is then calculated by iteratively re-calculating the artificial impedance pattern from the actual surface wave profile and the desired far field radiation pattern. An artificial impedance surface is determined by mapping the optimized artificial impedance pattern onto a representation of a physical surface.