Adaptive Array Processing for Multi-mission Phased Array Radar

As the use of phased array radars becomes more established for weather surveillance, adaptive array processing techniques will become more important to the weather radar community. Such techniques can be applied to phased array radars to improve angular resolution and also to suppress clutter compared to conventional beamforming methods. Thus, enhanced details of weather phenomena can be realized in terms of finer and better estimates of the reflectivity and radial velocity. This paper compares the performance of conventional beamforming to the performance of adaptive array processing based methods for a fully adaptive array and a partially adaptive array with six sidelobe-canceling elements, which is the configuration of the Multi-Mission Phased Array Radar (MPAR) of the National Weather Radar Testbed (NWRT) in Norman, Oklahoma. Different scenarios of fading clutter and clutter positions relative to the steering directions are considered. The simulated phased array concept uses a transmit beam that is wide in both angular directions to illuminate a large field of view and is thus termed an imaging radar. The receiver consists of individual antenna elements placed in a planar configuration. Time series signals for each antenna element are generated using a realistic radar simulator based on point-target scatterers, which flow and scatter according to a simulated environment produced from the Advanced Regional Prediction System (ARPS). Preliminary results show that, as expected, the performance of more sophisticated adaptive algorithms is superior compared to conventional beamforming, both in terms of angular resolution and clutter suppression.