Pulse pair beamforming and the effects of reflectivity field variations on imaging radars
Article first published online: 16 JUN 2004
Copyright 2004 by the American Geophysical Union.
Volume 39, Issue 3, June 2004
How to Cite
2004), Pulse pair beamforming and the effects of reflectivity field variations on imaging radars, Radio Sci., 39, RS3014, doi:10.1029/2002RS002843., , , , and (
- Issue published online: 16 JUN 2004
- Article first published online: 16 JUN 2004
- Manuscript Accepted: 6 MAY 2004
- Manuscript Revised: 3 MAY 2004
- Manuscript Received: 22 NOV 2002
- pulse pair beamforming;
- gradient variations;
- imaging radars
 Coherent radar imaging (CRI), which is fundamentally a beamforming process, has been used to create images of microscale, reflectivity structures within the resolution volume of atmospheric Doppler radars. This powerful technique has the potential to unlock many new discoveries in atmospheric studies. The Turbulent Eddy Profiler (TEP) is a unique 915 MHz boundary layer radar consisting of a maximum of 91 independent receivers. The TEP configuration allows sophisticated CRI algorithms to be implemented providing significant improvement in angular resolution. The present work includes a thorough simulation study of some of the capabilities of the TEP system. The pulse pair processor, used for radial velocity and spectral width estimation with meteorological radars, is combined with beamforming technique, in an efficient manner, to the imaging radar case. By numerical simulation the new technique is shown to provide robust and computationally efficient estimates of the spectral moments. For this study, a recently developed atmospheric radar simulation method is employed that uses the ten thousand scattering points necessary for the high resolution imaging simulation. Previous methods were limited in the number of scatterers due to complexity issues. Radial velocity images from the beamforming radar are used to estimate the three-dimensional wind field map within the resolution volume. It is shown that a large root mean square (RMS) error in imputed three-dimensional wind fields can occur using standard Fourier imaging. This RMS error does not improve even as SNR is increased. The cause of the error is reflectivity variations within the resolution volume. The finite beamwidth of the beamformer skews the radial velocity estimate, and this results in poor wind field estimates. Adaptive Capon beamforming consistently outperforms the Fourier method in the quantitative study and has been demonstrated to enhance the performance compared to the Fourier method.