Wind Profiler (WP) radars are used for 3-D vertical profiling of atmospheric winds. They transmit VHF/UHF band radio pulses towards vertical as well as off-vertical directions and receive the echoes from atmospheric targets. WP signal processor performs Doppler analysis on the received signal and derives wind velocities at different heights. This processing faces difficulty as the atmospheric echoes are very weak and the received signal is often contaminated by noise, clutter and Radio Frequency Interference (RFI). Wind profile estimation is greatly improved if all non-atmospheric echoes are removed at preprocessing stage. WP radar sessions generate large data volumes. The pre-processing of such a large data need to be handled by an automated program capable of removing the unwanted echoes. The present techniques for the removal of RFI and clutter are computationally complex and they require parameter changes for different radars and environmental conditions. These methods have limited utility when used for automated preprocessing. This paper presents an objective algorithm of RFI and clutter removal that is computationally simple and can be used on all radars and weather conditions without changing any parameters. The test results of this algorithm on the mesosphere-stratosphere-troposphere (MST) radar and Lower Atmospheric Wind Profiler (LAWP) radar, at Gadanki, are presented.
[1]
V. K. Anandan,et al.
An Autonomous Interference Detection and Filtering Approach Applied to Wind Profilers
,
2010,
IEEE Transactions on Geoscience and Remote Sensing.
[2]
P. Hildebrand,et al.
Objective Determination of the Noise Level in Doppler Spectra
,
1974
.
[3]
K. Moran,et al.
The Colorado Wind-Profiling Network
,
1984
.
[4]
Laura Bianco,et al.
Convective Boundary Layer Depth: Improved Measurement by Doppler Radar Wind Profiler Using Fuzzy Logic Methods
,
2002
.
[5]
Peter T. May,et al.
An Examination of Wind Profiler Signal Processing Algorithms
,
1989
.
[6]
Warner L. Ecklund,et al.
A Fuzzy Logic Method for Improved Moment Estimation from Doppler Spectra
,
1998
.
[7]
Ramachandra Reddy Gudheti,et al.
MST Radar Signal Processing Using Wavelet-Based Denoising
,
2009,
IEEE Geoscience and Remote Sensing Letters.
[8]
Corinne S. Morse,et al.
The NIMA Method for Improved Moment Estimation from Doppler Spectra
,
2002
.
[9]
Peter T. M Ay,et al.
NOTES AND CORRESPONDENCE Reducing the Effect of Ground Clutter on Wind Profiler Velocity Measurements
,
1998
.