Abstract
Boundary layer radar (L-band) wind profilers frequently encounter a significant problem arising from the contamination of intermittent clutter, produced by seasonal and nocturnal migrating birds, which often yields erroneous wind velocity and boundary layer information. Classical harmonic wavelet transforms (HWTs) are inadequate in removing the transient clutter contamination under certain conditions, particularly when the clutter is significant. We implemented an adaptive complex harmonic discrete wavelet transform with an advanced statistical method to overcome the shortcomings of the classical wavelet method. This algorithm effectively eliminates the bird contamination even where the classical method fails. Finally, a multiple peak-picking (MPP) algorithm was added to select true atmospheric signals and estimate accurate moments. The obtained wind velocity measurements were compared with those derived using the conventional method and validated with global positioning system radiosonde winds. The comparison shows that the proposed method is more effective than the conventional one.
Original language | English |
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Article number | 8752101 |
Pages (from-to) | 8546-8556 |
Number of pages | 11 |
Journal | IEEE Transactions on Geoscience and Remote Sensing |
Volume | 57 |
Issue number | 11 |
DOIs | |
State | Published - Nov 2019 |
Keywords
- Clutter
- signal processing
- wavelet transform
- wind profiler