Abstract
Abstract. A new signal processing method is presented for the suppression of intermittent clutter echoes in radar wind profilers. This clutter type is a significant problem during the seasonal bird migration and often results in large discrepancies between profiler wind measurements and independent reference data. The technique presented makes use of a discrete Gabor frame expansion of the coherently averaged time series data in combination with a statistical filtering approach to exploit the different signal characteristics between signal and clutter. The rationale of this algorithm is outlined and the mathematical methods used are presented in due detail. A first test using data obtained with an operational 482 MHz wind profiler indicates that the method outperforms the previously used clutter suppression algorithm.
Highlights
Radar wind profilers (RWP) were developed from MSTRadars (Van Zandt, 2000) and have become standard instruments for measuring wind velocities in the atmosphere
Such have been presented by various authors: Wilczak et al (1995) described the distinct characteristic of bird contaminated I and Q data when seen in an A-scope display, but the shown time series taken with a 924 MHz RWP is only 0.5 s long, which is too short to see its essential characteristics
We have dealt with wind profiler signals obtained during bird migration and shown, how the signals can be decomposed into a time-frequency representation
Summary
Radar wind profilers (RWP) were developed from MSTRadars (Van Zandt, 2000) and have become standard instruments for measuring wind velocities in the atmosphere. Teschke: Advanced intermittent clutter filtering for radar wind profiler became obvious that especially echoes from migrating birds can be a serious issue in wind profiling (Ecklund et al, 1990; Barth et al, 1994). If present, such spurious signals can cause a significant deterioration of the quality of the derived winds. We propose a new signal-clutter separation method that attempts to meet these objectives It is based on a redundant frame decomposition of the time series followed by the statistical filtering approach suggested by Merritt (1995).
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