Modulation patterns for surface scattering antennas

• US 9,711,852 B2
• Filed: 11/21/2014
• Issued: 07/18/2017
• Est. Priority Date: 06/20/2014
• Status: Active Grant

• Current Assignee: The Invention Science Fund I, L.L.C. (Intellectual Ventures LLC)
• Original Assignee: The Invention Science Fund I, L.L.C. (Intellectual Ventures LLC)
• Inventors: Chen, Pai-Yen, Ebadi, Siamak, Hunt, John Desmond, Landy, Nathan Ingle, Perque, Jr., Milton, Machado, Melroy, Driscoll, Tom, Smith, David R., Urzhumov, Yaroslav A.
• Primary Examiner(s): Nguyen, Hoang
• Assistant Examiner(s): BOUIZZA, MICHAEL M
• Application Number:
  US14/549,928
• Publication Number:
  US 20150372389A1
• Time in Patent Office: 970 Days
• CPC Class Codes: H01Q 11/02 Non-resonant antennas, e.g. travelling-wave antenna Yagi antennas H01Q19/30
• CPC Class Codes: H01Q 13/20 Non-resonant leaky-waveguide or transmission-line antennas; Equivalent structures causing radiation along the transmission path of a guided wave
• CPC Class Codes: H01Q 3/44 varying the electric or magnetic characteristics of reflecting, refracting, or diffracting devices associated with the radiating element

Abstract

Modulation patterns for surface scattering antennas provide desired antenna pattern attributes such as reduced side lobes and reduced grating lobes.

Claims

1. A method, comprising:

discretizing a hologram function for a surface scattering antenna; and

identifying an antenna configuration that reduces artifacts attributable to the discretizing.

2. The method of claim 1, further comprising:

adjusting the surface scattering antenna to the identified antenna configuration.

3. The method of claim 1, further comprising:

operating the surface scattering antenna in the identified antenna configuration.

4. The method of claim 1, further comprising:

storing the identified antenna configuration in a storage medium.

5. The method of claim 1, wherein the surface scattering antenna defines an aperture and the discretizing includes identifying a discrete plurality of locations on the aperture for a discrete plurality of scattering elements of the surface scattering antenna.

6. The method of claim 5, wherein the discretizing includes identifying a discrete set of states for each of the scattering elements corresponding to a discrete set of function values at each of the locations of the scattering elements.

7. The method of claim 6, wherein the identifying of the antenna configuration includes:

selecting, for the plurality of locations, a plurality of function values from the discrete set of function values, where the selected plurality optimizes a desired cost function for an antenna pattern of the antenna.

8. The method of claim 7, wherein the selecting that optimizes the desired cost function is a selecting with a discrete optimization algorithm.

9. The method of claim 8, wherein the discrete set of function values is a binary set of function values.

10. The method of claim 8, wherein the discrete set of function values is a grayscale set of function values.

11. The method of claim 7, wherein the selecting that optimizes the desired cost function is a selecting with a continuous optimization algorithm.

12. The method of claim 7, wherein the selecting that optimizes the desired cost function includes evaluating the desired cost function for a sequence of trials, each trial consisting of a plurality of trial function values for the plurality of locations, where each of the trial function values selected from the discrete set of function values.

13. The method of claim 12, wherein the evaluating of the desired cost function for the sequence of trials includes, for each trial in the sequence of trials:

identifying a trial antenna configuration corresponding to the plurality of trial function values;

performing a full-wave simulation of the trial antenna configuration; and

evaluating the desired cost function with results of the full-wave simulation.

14. The method of claim 12, wherein the evaluating of the desired cost function for the sequence of trials includes, for each trial in the sequence of trials:

identifying a trial antenna configuration corresponding to the plurality of trial function values;

measuring a test antenna in the trial antenna configuration; and

evaluating the desired cost function with data from the measuring.

15. The method of claim 7, wherein the cost function maximizes a gain of the antenna in a selected direction, maximizes a directivity of the antenna in a selected direction, minimizes a half-power beamwidth of a main beam of the antenna pattern, minimizes a height of a highest side lobe relative to a main beam of the antenna pattern, or minimizes a height of a highest grating lobe relative to a main beam of the antenna pattern.

16. A method of controlling an surface scattering antenna with a plurality of adjustable scattering elements, comprising:

reading an antenna configuration from a storage medium, the antenna configuration being selected to reduce artifacts attributable to a discretization of a hologram function; and

adjusting the plurality of adjustable scattering elements to provide the antenna configuration.

17. The method of claim 16, further comprising:

operating the antenna in the antenna configuration.

18. The method of claim 16, wherein the adjustable scattering elements are adjustable between a discrete set of states corresponding to a discrete set of function values at each location in a plurality of locations for the plurality of adjustable scattering elements.

19. The method of claim 18, wherein the antenna configuration is selected to optimize, in a space of antenna configurations, a desired cost function for the antenna configuration.

20. The method of claim 19, wherein the antenna configuration is selected with a discrete optimization algorithm.

21. The method of claim 20, wherein the discrete set of function values is a binary set of function values.

22. The method of claim 20, wherein the discrete set of function values is a grayscale set of function values.

23. The method of claim 19, wherein the antenna configuration is selected with a continuous optimization algorithm.

24. The method of claim 19, wherein the antenna configuration is selected with an optimization algorithm that includes:

evaluating the desired cost function for a sequence of trial antenna configurations.

25. The method of claim 24, wherein the evaluating of the desired cost function for the sequence of trials includes, for each trial antenna configuration in the sequence of trial antenna configurations:

performing a full-wave simulation of the trial antenna configuration; and

evaluating the desired cost function with results of the full-wave simulation.

26. The method of claim 24, wherein the evaluating of the desired cost function for the sequence of trials includes, for each trial antenna configuration in the sequence of trial antenna configurations:

measuring a test antenna in the trial antenna configuration; and

evaluating the desired cost function with data from the measuring.

27. The method of claim 19, wherein the cost function maximizes a gain of the antenna in a selected direction, maximizes a directivity of the antenna in a selected direction, minimizes a half-power beamwidth of a main beam of the antenna pattern, minimizes a height of a highest side lobe relative to a main beam of the antenna pattern, or minimizes a height of a highest grating lobe relative to a main beam of the antenna pattern.