Vaisala RVP900 - Page 199

GMAP Step Description
Step 4: Replace Clutter Points The assumption of a Gaussian weather spectrum now comes into play to
replace the points that have been removed by the clutter filter.
There are two cases depending on how the noise level is determined under
Step 2, that is, the dynamic noise case and the fixed noise level case.
Dynamic noise level case: From Step 2, we know which spectrum
components are noise. From Step 3 we know which spectrum components
are clutter. Presumably, everything that is left is weather signal. An inverse
DFT using only these components is performed to obtain the
autocorrelation at lags 0, 1. This is very computationally
ecient since there
are typically few remaining points and only the first two lags need be
calculated. The pulse pair mean velocity and spectrum width are calculated
using the Gaussian model.
2
Note that since the noise has already been
removed, there is no need to do a noise correction. The Gaussian model is
then applied using the calculated moments to determine a substitution
value for each of the spectrum components that were removed in Step 3.
In the case of overlapped weather as shown in the GMAP example, the
replacement power is typically too small. For this reason, the algorithm
recomputes R0 and R1 using both the observed and the replacement points
and computes new replacement points.
This procedure is done iteratively until the power dierence between two
successive iterations is less than 0.2 dB and the velocity dierence is less
than 0.5% of the Nyquist interval.
In summary of this step, the Gaussian weather model is used to repair the
filter bias, that is, the damage that is caused by removing the clutter points.
An IIR filtering approach makes no attempt to repair filter bias, rather the
filter "digs a hole" into overlapped weather.
Step 5: Check for Appropriate
Window and Recalculate the
Moments, if necessary
The clutter power is known from the spectrum components that were
removed in Step 3. Since the weather spectrum moments and the noise are
also known from Step 4, the CSR can be calculated. The value of the CSR, is
used to decide whether the Hamming window is the most appropriate.
The end result is that very weak clutter is processed using a rectangular
window, moderate clutter a Hamming window, while severe clutter requires
a Blackman window. Note that if no clutter were removed in Step 3, then the
spectrum is processed with a rectangular window.
The
benefit of adaptive windowing is that the least aggressive window is
used for the calculation of the spectrum moments, resulting in the minimum
variance of the moment estimates
GMAP Configuration
The mf command in the dspx TTY setups is used to configure GMAP filters. In the section for
the spectrum
filters select filter "Type 2" and specify the width of the ground clutter in m/s.
This width is determined largely by your antenna rotation rate, so you should con-figure
several widths to deal with the dierent rotation rates in your operational scenario. An
example might be
filters indexed 1-5 corresponding to widths from 0.1 ... 0.5.
A good practice is to make a scan on a clear day while using ascope or other utility and
observe the width of the clutter for your scan rates. You must turno the clutter filtering to
do this (select filter 0 for the all pass filter).
Chapter 7 – Processing Algorithms
197