Name of the Speaker: Prajosh K P (EE17D044)
Name of the Guide: Dr. Uday Khankhoje
Venue: CSD 308
Date/Time: September 2nd, 2022 at 11.00 AM
Faulty elements in a phased array antenna lead to the undesired radiation pattern and substandard system performance. Therefore, fault diagnosis in a phased array is an inevitable task to ensure the proper functioning of a communication system. A compressive sensing-based inverse problem is formulated to recover the sparse solutions and locate the faulty elements from the minimum number of far-field measurements. We propose a diagnosis method from fixed probe measurements and varying excitations. The non-convex lp norm (0 < p <1) minimization problem is solved using the IRL1-ADMM algorithm. Further reduction in the number of measurements is guaranteed by optimizing the excitations to minimize the mutual coherence of the system measurement matrix.
In antenna far-field analysis, the mutual coupling is often neglected to simplify the problem and uses isolated patterns in pattern multiplication. Taking a different route, we incorporate the effect of mutual coupling and demonstrate successful fault recovery even in such cases. We take the measurements of a planar dipole array from a full-wave solver and comprise the effects of mutual coupling in fault diagnosis using two coupling models- 1) average embedded pattern and 2) port-level coupling matrix approach. We evaluate the performance of coupling models against the isolated pattern model.
Our further research in the fault diagnosis in antenna array is extended to the case where the reference pattern of a fault-free array is unavailable. A novel method to quantify the mutual coupling from compressive measurements based on a combination of sparse recovery and low- rank matrix decomposition is also proposed.
We generalize the proposed method by mentioning its applicability in fault diagnosis of a multicarrier precoding system under operation. We show that, in multicarrier hybrid (digital precoding) architectures, a small part of the available spectrum can be used for fault detection while the rest is used for regular operation.