Optimal Gabor-Frame-Expansion-Based Intermittent-Clutter-Filtering Method for Radar Wind Profiler

Intermittent clutter signals are frequently observed by radar wind profilers during the seasonal bird migration. A novel statistical filtering algorithm based on a simultaneous time-frequency analysis of the profiler's raw data was recently proposed to address shortcomings of existing methods. The foundation of this method is a Gabor frame expansion of the complex time series of the demodulated receiver voltage. In this paper, two objective criteria are suggested to obtain an optimal setup for the discrete Gabor frame expansion from the multitude of possibilities: first, the choice of almost-tight frames for a predefined maximum redundancy and second, the requirement that the analyzing bandwidth of the used Gaussian window function should provide a simultaneously sparse representation of both atmospheric signal components and intermittent clutter. The question of optimal sampling settings, especially dwell time, for a maximum reduction of bird interference is also discussed. Using data obtained during intense bird migration events it is shown that a combination of filtering and quality control of the result is required to prevent the occurrence of significant systematic and correlated errors in the final wind measurement.