User's Manual Part 2

Processing Algorithms (draft)
RVP8 User’s Manual
April 2003
5–17
5.2.9 Clutter Correction (CCOR threshold)
In addition to calculating the R
0
, R
1
and optional R
2
autocorrelation terms, which are based on
filtered time series data, the RVP8 also computes T
0
which is the total unfiltered power. By
comparing the total filtered and unfiltered powers at each range bin, a clutter power, and hence a
clutter correction, for that bin can be derived. The clutter correction is defined as,
CCOR + 10 log
S
C ) S
+ 10 log
1
CSR ) 1
where S is the weather signal power, C is the clutter power and CSR is the clutter-to-signal
ratio. The algorithm for calculating CCOR depends on whether the optional
R
2
autocorrelation
lag is computed as described below.
R
0
, R
1
Clutter Correction
In this case CCOR is estimated from,
CCOR
est
+ 10 log
ƪ
R
0
T
0
ƫ
+ 10log
ƪ
S ) N
C ) S ) N
ƫ
+ 10logƪ
1 )
1
SNR
CSR ) 1 )
1
SNR
ƫ
Here, the expression is strictly valid only when the signal-to-noise ratio
(SNR=S/N) is large. Thus when the 2-lag approach is used, the clutter corrections are not
as accurate for weak weather signals. However, the error is typically less than 3 dB.
R
0
, R
1
, R
2
Clutter Correction
In this case there is enough information to compute the clutter signal and noise power inde-
pendently. The algorithm for CCOR is:
CCOR
est
+ 10 log
S
C ) S
+ 10 log
1
CSR ) 1
The clutter power is computed from:
C + T
o
* R
o
+
[
C ) S ) N
]
*
[
S ) N
]
The signal power S is then computed from:
S + | R
1
| exp
p
2
W
2
2
W is the width that has been previously calculated. This approach yields more accurate re-
sults for the clutter correction in the case of a low SNR.