When RVP900 enters a new internal processing mode (time series, FFT, PPP, and so on), the
burst power estimator is reinitialized from the level of the first pulse encountered, and an
additional pipeline delay is introduced to allow the estimator to completely settle. Valid
corrected data are produced even when RVP900 alternates rapidly between dierent data
acquisition tasks, for example, in a multi-function Ascope display. The additional pipeline
delay does not aect the high-speed performance when RVP900 runs continuously in a
single mode.
For amplitude correction to be applied, the instantaneous Burst/COHO signal level must
exceed the minimum valid burst power
specified in the Mb setup section. If that level is not
met, for example, if the transmitter is turned o, then no correction is performed. The
amplitude correction feature "gets out of the way" when receiver-only tests are being
performed.
The maximum applied correction is ±5 dB. If the burst power in a given pulse is more than
5 dB above the mean, or less than 5 dB below it, then the correction is clamped at those
limits. The power variation of a typical transmitter easily contained within this interval (it is
typically less than 0.3 dB).
7.3 Time Series Signal Processing
Radar time series data (also called linear "video" or I and Q) processing is done to obtain
the meteorologically significant moment parameters: reflectivity, total power, velocity,
width, signal quality index, clutter power correction, and optional polarization variables.
The time series are the starting point for all calculations performed in RVP900.
The time series synthesized by the FIR
filter consist of an array of complex numbers:
=
+
= 1, 2, 3, ...,
where j is - 1
1/2
.
Time Series Signal Processing Categories
There are two broad categories of time series signal processing:
• Time Domain Processing using the I and Q samples directly to calculate
"autocorrelations" and then using the autocorrelations to compute the moments.
This is used by many systems since the algorithms are very ecient requiring minimal
storage and computational power. However, time domain algorithms are generally not
adaptive or very
flexible.
• Frequency Domain Processing using the I and Q samples to calculate a Doppler power
spectrum and then applying algorithms, such as clutter filtering or second trip echo
filtering/extraction, in the frequency domain. The Doppler spectrum is then inverted to
obtain the autocorrelation functions and these are used to calculate the moments. The
frequency domain is well suited to more complex adaptive algorithms, that is, where
the processing algorithm is optimized for the data
Support Time Series Processing Modes
RVP900 supports the following "major modes" or processing modes to process the time
series
Chapter 7 – Processing Algorithms
183
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