Robust Beamforming for X-Band Phased Array Weather Radar

Phased array weather radars (PAWRs) are increasingly becoming viable because of their operational advantage in the agile scanning of large precipitation volumes without any mechanical motion and an efficient beam scheduling-and-tracking. Conventional PAWR estimates precipitation profiles through Fourier beamforming. However, this method is not robust to interference, clutter and mismatch in steering vectors. In this work, we offset these disadvantages by using advanced robust and adaptive beamformers in PAWR. The volumetric nature of the precipitation target makes direct application of these techniques to PAWR non-trivial. We validate our methods through data collected from the solid-state low-power X-band PAWR developed at IIT Palakkad.