Application of Machine Learning for Antenna Array Failure Analysis

In this work, a machine learning technique is used to detect and locate failed elements in an antenna array. The approach allows for detection and location of up to two simultaneous failures. The far-field pattern is sampled in different ways to form multiple datasets. These datasets are then used to train a feedforward neural network, and the results are compared according to accuracy, training time and the number of samples in the training data.