Vaisala RVP900

USER’S MANUAL__________________________________________________________________
216 _________________________________________________________________ M211322EN-D
6.3 Autocorrelation R(n) Processing
6.3.1 Point Clutter Remover
The first step in autocorrelation processing is the optional removal of point
clutter. "Point Clutter" is a non-meteorological target of very narrow range.
These are either small strong targets, such as airplanes, ships, or other
moving objects.
There are 2 adjustable parameters for the point clutter algorithm:
- TCM Point clutter threshold factor
- Offset Point clutter range offset in bins
The first pass called "Clutter detection" is to screen all range bins to see if
their Doppler filtered power exceeds the normal level before and after in
range. In other words, flag all bins if:
These flag bits are output in the optional flag word. The second pass called
"Clutter sensoring" involves linearly interpolating all the autocorrelation
values in range over the interval of clutter bins including the offsets at
either sides if the offset is larger than 1:
Note that the same thing is done for all the filtered autocorrelations and
crosscorrelations (lagged moments R
1
, R
2
, and dual-polarization
crosscorrelations) as soon as any of the filtered autocorrelation R
0
H
, R
0
V
,
or R
0
HV
exceeds the threshold. The unfiltered autocorrelations (total
power) T
0
H
, T
0
V
, and T
0
HV
are conserved.
R
0
r TCM*R
0
r Offset– and R
0
r TCM*R
0
rOffset+
R
0
r
r
end
r–
r
end
r
start
–
--------------------------------



*
R
0
r
start

rr
start
–
r
end
r
start
–
--------------------------------



*
R
0
r
end
 , where r+ r
start
, r
end
==