Motion-Compensated Steering: Enhanced Azimuthal Resolution for Polarimetric Rotating Phased Array Radar
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Motion-Compensated Steering: Enhanced Azimuthal Resolution for Polarimetric Rotating Phased Array Radar

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  • Journal Title:
    IEEE Transactions on Geoscience and Remote Sensing
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    The rotating phased array radar (RPAR) is an architecture that could improve the capabilities of the current weather surveillance radar--1988 Doppler (WSR-88D) operational network and is likely to be more affordable than other candidate PAR architectures. However, continuous antenna rotation coupled with the need to perform coherent processing of multiple samples results in a degraded effective beamwidth (referred to as beam smearing) compared to architectures based on stationary antennas. The RPAR's beam agility can be exploited to reduce beam-smearing effects by electronically steering the beam on a pulse-to-pulse basis within the coherent processing interval. That is, the motion of the antenna can be compensated to maintain the beam pointed at the center of resolution volume being sampled. This motion-compensated steering (MCS) could reduce the effects of antenna motion and lead to a reduction in the effective beamwidth. The purpose of this article is to present and demonstrate the MCS technique for a dual-polarization RPAR system. In this article, we provide a formulation for the MCS technique, simulations to quantify its performance in mitigating beam-smearing effects, its impacts on the quality of dual-polarization radar-variable estimates, and a practical implementation on the National Severe Storms Laboratory's Advanced Technology Demonstrator (ATD) system. Experiments were carried out using two alternative concepts of operations (CONOPS) described in this article. Results show that a system designed with sufficient pointing accuracy can be operated as an RPAR using MCS, and the impact on radar-variable estimates is comparable to that obtained when operating the same system as a stationary PAR.
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    IEEE Transactions on Geoscience and Remote Sensing
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