3-D hurricane boundary layer wind retrieval algorithm for airborne Doppler radar measurements
This paper presents a 3D boundary layer wind retrieval algorithm for airborne Doppler radar measurements of precipitation inside hurricanes. The data was collected, inside Hurricane Lili during NOAA's 2002 Atlantic Hurricane Ocean Winds Field Experiment with University of Massachusetts's newly developed Imaging Wind and Rain Airborne Profiler. Two forms of Kalman filters for 3D wind retrieval are analyzed for accuracy using simulations. Preliminary results of the actual 3D wind estimates using the chosen algorithm were obtained and compared with simultaneous and independent wind vector measurements by GPS dropwindsondes, surface wind speed measurements by a microwave radiometer and flight level wind vector measurements
Preliminary results of 3D hurricane boundary layer wind estimation with multilook Doppler radar measurements of the precipitation
This paper presents preliminary results of the 3D-wind retrieval algorithm developed for the multi-look airborne Doppler radar measurements using various forms of Kalman filters. The data was collected inside Hurricane Lili during NOAA's 2002 Atlantic Hurricane Ocean Winds Field Experiment with University of Massachusetts's newly developed Imaging Wind and Rain Airborne Profiler (IWRAP). Two forms of Adaptive Kalman filter are presented for 3-D wind retrieval. Simulations of different wind field and radar parameters are made to investigate the performance of the selected filter. Preliminary results of the actual 3-D wind estimates are then obtained and compared with simultaneous and independent wind vector measurements by GPS dropwindsondes, surface wind speed measurements by a microwave radiometer and flight level wind vector measurements.
FPGAs make a radar signal processor on a chip a reality
Radar signal processors heavily tax the capabilities of conventional microprocessor based signal processing systems. Higher performance systems using custom silicon cost too much for the typically small production volumes, and are not flexible enough for research applications. Field programmable gate arrays offer the performance of custom silicon while maintaining the economies and flexibility of the microprocessor based solutions. Recent devices possess the density and performance to realize a complete radar signal processor in a single FPGA, including complex down-conversion of the IF to base-band. Performing the down-conversion and matched filtering in the FPGA eliminates the specialty chips previously needed for these functions, making it possible to use commercially available FPGA boards. Our system packs 4 channels into a pair of FPGAs. Each channel (a demodulator, a matched filter and a Doppler pulse pair processor) executes over 5 billion multiplies per second.