Vaisala RVP900 - Figure 42 Variable Width Clutter Filter

dB Power
Velocity
dB Power
dB Power
Vu
–
Vu
+
0
Spectrum with ground clutter
Remove 3 interior points
Use slope to extend the clutter bound-
ary. Then find the minimum of the 2
edge points and interpolate.
Figure 42 Variable Width Clutter Filter
In the figure, the minimum number of points to reject is set to 3. The filter starts at zero
velocity and checks the slope to determine the point at which the power starts to increase.
In the example, this results in the
filter being extended by one point on the right. Note that
there is a selectable maximum number of points that the
filter "hunts". The use of the edge
points for interpolation is identical to the fixed width case.
This filter allows users to specify a narrower nominal filter than the fixed width case and
then when the clutter is strong, this width is extended by the algorithm (the "hunt"). The
interpolation attempts to preserve any overlapped clutter and weather.
7.3.5.3 Gaussian Model Adaptive Processing (GMAP) Filtering
GMAP processing has the following advantages as compared to fixed width frequency
domain filters or time domain filtering such as the IIR approach:
• The width adapts in the frequency domain to adjust for the eects of PRF, number of
samples and the absolute amplitude of the clutter power. This means that minimal
operator intervention is required to set the
filter.
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