Beamforming algorithms with null steering

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Albert
Albert le 6 Fév 2022
Hi!
I have an antenna made of N linear elements forming an array (N = 3). I want to compute the steering vector so that the maximum of the array factor points to the boresight (or a direction close-by), let's say at 0º, but I want to place a null at a certain direction (say at 15º), but I want to place this null symmetrically with respect to the main beam (so at +/- 15º). I think analytically this is difficult to achieve (one main direction and one null it is ok but not the two nulls) and probably a genetic algorithm solution would be best suited. However I'm not sure this is the best approach using Matlab (and how to use it) or if there are better built-in beamformers for this purpose (e.g. MVDR). Any clue on this topic would help me very much.
Thank you very much!

Réponses (1)

Maneet Kaur Bagga
Maneet Kaur Bagga le 7 Jan 2024
Hello,
As per my understanding, designing an antenna array pattern with a specific main lobe direction and nulls at specified angles to create symmetric nulls with respect to the main beam involves optimization algorithms like genetic algorithms and analytical methods that might involve the use of beamforming techniques such as Minimum Variance Distortionless Response (MVDR).
The workaround for above problem could involve a hybrid approach where starting with an analytical solution (like MVDR with constraints) and then refining the solution using an optimization algorithm (like Genetic Algorithm) to fine-tune the array pattern could potentially offer a good balance between computational efficiency and the flexibility to meet design specifications.
Please refer to the steps below to implement the same in MATLAB.
  1. Use the Phased Array System Toolbox to model array and the desired pattern.
  2. Apply the MVDR beamforming technique with constraints for the nulls.
  3. If the MVDR solution doesn't meet the requirements, use the Genetic Algorithm to optimize the element weights or phases further.
Please refer to the following MATLAB Documentation for understanding of the implementation of above algorithm:
Hope this helps!

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