Tuning for optimal performance

Secondary SQI threshold

In standard Doppler processing, an SQI threshold is normally not applied to reflectivity data, because it would cause that data to be rejected in regions of high spectral width. However, in the random phase mode, if SQI is applied to reflectivity or dual-polarization data, we need to do it, especially in random phase processing, because reflected power can only be assigned to a particular trip when it is coherent within that trip. Incoherent echoes, regardless of their strength, cannot be placed in either trip.

An SQI threshold is required to qualify reflectivity and dual-polarization data in all the processing modes. RVP10 defines a secondary SQI threshold SQI2 that is computed from the standard threshold value as:

where Slope and Offset are the secondary SQI threshold parameters defined in the Mf setup section.

The factory default values are (Slope = 0.50) and (Offset = 0.05), that is, the secondary threshold is a little less than half of the standard value.

The algorithms check whether the SQI of each recovered trip is less than the secondary SQI threshold, and if so, the LOG portion of the data are rejected. This SQI test is necessary for a clean LOG picture, but we need to use a more permissive (lower) threshold value than would usually be applied to the reflectivity and dual pol data alone.

The Slope and Offset values should be adjusted so that the density of speckles in LOG data is approximately the same as the density of speckles in FFT velocity data for a given primary SQI value. You may then adjust the primary SQI threshold to achieve the appropriate trade-off of speckles versus sensitivity for your system in all modes of operation. Even with proper adjustment, it is normal for dual-polarization, dBZ and dBT data to show gaps in regions of weather that have high turbulence or shear when SQI threshold is applied to that data. These dropouts usually match similar gaps in the velocity and width data, both of which are traditionally thresholded by SQI.

Maximum power ratio between trips

The adaptive filtering that is performed on the data for each trip greatly extends the visibility of a weak echo that is overlapped with a much stronger one. In practice, the filtering process is often able to remove 25 ... 35 dB of dominant power in order to reveal a much weaker echo in the other trip. The performance depends on many factors, primarily the spectral width of the dominant echo, and the overall stability of the radar system.

The difficulties of removing a dominant "other trip" echo from a weather signal are analogous to the challenge of removing a dominant clutter target from that same signal. In both cases we are trying to extract a weak weather signature using a filtering procedure that relies on the spectral confinement of the stronger signal.

The Clutter-to-Signal Ratio (CSR) parameter can be adjusted to control sub-clutter visibility. Just as the CSR applies to the clutter filters, it can also be used to place similar limits on the depth of visibility of the adaptive filters.

Example: RVP10 is operating in random phase mode at a PRF of 1500Hz, and is observing widespread weather having uniform intensity in both the first 100-km trip and the second 100-km trip. If the CSR was set too conservatively at only 15 dB, then the algorithm would generally be blind to the second-trip weather in the range interval 100 km ... 100 km.

The explanation for this can be found in the 1/r² geometric correction for weather echo intensity. At ranges less than 17.8 km, the first trip weather would generally dominate the second trip weather by more than 15 dB. Thus, the initial 17.8 km ring of second trip data would be rejected by the CSR criteria. However, if the CSR were increased to 30 dB, then the size of this missing ring would be reduced to only 3.2 km.

If the CSR is set too low, there is an abrupt ring of missing data in the beginning of the second trip. If set too high, there are speckles and other spurious effects within this same interval. The optimum setting should strike a balance between these two effects.

R1 vs. R2 algorithms

The random phase algorithms for adaptive filtering and separation of trips relies on having the best possible information about the weather's SNR and spectral width. Thus, the R2 Doppler algorithms are always used, regardless of the setting of the R1/R2 flag in the operational parameters.

Random phase and Dual PRF

The random phase processing works seamlessly with the dual PRF processing to provide advanced range and velocity ambiguity resolution. Both the first and second trip echoes can be recovered and displayed to a maximum range of 2X the unambiguous range corresponding to the high PRF.

For optimum performance, the 2D 3x3 speckle filter should be used to smooth the second trip seams that occur for each ray. In fact, this smoothing of the second trip seam makes the dual PRF random phase mode work even better than the single PRF random phase.

For more information, see Random phase second trip processing algorithm.