Mobile weather radars often utilize rapid-scan strategies when collecting observations of severe weather. Various techniques have been used to improve volume update times, including the use of agile and multibeam radars. Imaging radars, similar in some respects to phased arrays, steer the radar beam in software, thus requiring no physical motion. In contrast to phased arrays, imaging radars gather data for an entire volume simultaneously within the field of view (FOV) of the radar, which is defined by a broad transmit beam. As a result, imaging radars provide update rates significantly exceeding those of existing mobile radars, including phased arrays. The Advanced Radar Research Center (ARRC) at the University of Oklahoma (OU) is engaged in the design, construction, and testing of a mobile imaging weather radar system called the atmospheric imaging radar (AIR). Initial tests performed with the AIR demonstrate the benefits and versatility of utilizing beamforming techniques to achieve high spatial and temporal resolution. Specifically, point target analysis was performed using several digital beamforming techniques. Adaptive algorithms allow for improved resolution and clutter rejection when compared to traditional techniques. Additional experiments were conducted during two severe weather events in Oklahoma. Several digital beamforming methods were tested and analyzed, producing unique, simultaneous multibeam measurements using the AIR.
The progression of phased array weather observations, research, and planning over the past decade has led to significant advances in development efforts for future weather radar technologies. However, numerous challenges still remain for large-scale deployment. The eventual goal for phased array weather radar technology includes the use of active arrays, where each element would have its own transmit/receive module. This would lead to significant advantages; however, such a design must be capable of utilizing low-power, solid-state transmitters at each element in order to keep costs down. To provide acceptable sensitivity, as well as the range resolution needed for weather observations, pulse compression strategies are required. Pulse compression has been used for decades in military applications, but it has yet to be applied on a broad scale to weather radar, partly because of concerns regarding sensitivity loss caused by pulse windowing. A robust optimization technique for pulse compression waveforms with minimalistic windowing using a genetic algorithm is presented. A continuous nonlinear frequency-modulated waveform that takes into account transmitter distortion is shown, both in theory and in practical use scenarios. Measured pulses and weather observations from the Advanced Radar Research Center’s dual-polarized PX-1000 transportable radar, which utilizes dual 100-W solid-state transmitters, are presented. Both stratiform and convective scenarios, as well as dual-polarization observations, are shown, demonstrating significant improvement in sensitivity over previous pulse compression methods.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.