US 12,457,047 B2
Method and device for detecting and localizing faults in an antenna array, and test system
Marwa Sai, Munich (DE); Andrew Schaefer, Oberhaching (DE); Benoit Derat, Munich (DE); and Adam Tankielun, Ottobrunn (DE)
Assigned to Rohde & Schwarz GmbH & Co. KG, Munich (DE)
Filed by Rohde & Schwarz GmbH & Co. KG, Munich (DE)
Filed on Feb. 9, 2023, as Appl. No. 18/166,559.
Prior Publication US 2024/0275503 A1, Aug. 15, 2024
Int. Cl. H04B 17/17 (2015.01); H01Q 21/24 (2006.01)
CPC H04B 17/17 (2015.01) [H01Q 21/24 (2013.01)] 13 Claims
OG exemplary drawing
 
1. A computer-implemented method for detecting and localizing faults in an antenna array, comprising the steps:
performing fault detection on the antenna array to identify the presence of at least one faulty antenna element of the antenna array, wherein the fault detection is performed using a machine learning technique;
determining whether the antenna array is faulty or non-faulty, based on a result of the performed fault detection; and
localizing the at least one faulty antenna element if the antenna array is determined to be faulty, using a machine learning technique;
wherein the steps of performing fault detection and of localizing the at least one faulty antenna element are based on over-the-air measurement data generated by at least one measurement antenna positioned at multiple sampling points around the antenna array; and
wherein the machine learning technique used for performing fault detection and the machine learning technique used for localizing the at least one faulty antenna element comprise at least one pre-trained deep neural network model outputting fault detection and localization results used to adjust antenna element weights to restore a target radiation pattern.