Phased array antennas are essential components of communication systems. Faulty elements in a phased array antenna lead to undesired radiation patterns and substandard system performance. Therefore, fault diagnosis in a phased array is an inevitable task to ensure the proper functioning of a communication system. In our work, we show how to diagnose faults in an array with an easy measurement setup and comparatively less computational complexity. We solve an inverse problem for locating the faulty elements in a phased array from its complex field measurements. We assume sparsity in the solution by considering only a few elements are faulty, and opted compressive sensing for solution recovery. Compressive sensing promises to recover sparse solutions from the minimum number of measurements. In addition, we focused on the sensing matrix design by optimizing the excitations, which can further reduce the number of measurements required for fault diagnosis.



The electromagnetic interaction between the array elements is called mutual coupling, which is often neglected in most existing methods for beamforming and fault diagnosis. We show how to incorporate mutual coupling in the proposed framework for fault diagnosis. Afterwards, we propose a reference-free fault diagnosis method that does not require any prior information, such as the field of a fault-free array (healthy array), element patterns, standard coupling models, and so on. The online fault diagnosis in hybrid beamformers is also presented in our work, where the fault diagnosis is done when the system is in operation.



We validated the proposed methods using full-wave simulations in the Matlab antenna toolbox by taking examples of dipole and loop antenna arrays. The results show strong agreement with our expectations and stress the efficiency of our methods in a practical scenario.