Terrain presents one of the most pressing challenges of radar sensing accuracy. Mountains, buildings and other natural and man-made structures can cause erroneous hydrometeor detection as the radar signal reaches them, and is reflected back the radar’s receiver. Clutter filtering is used to reduce inaccurate radar returns, enabling clean, more precise display of actual weather targets.
Available through an exclusive licensing agreement with the University of Oklahoma, the CLEAN-AP™ filtering process used in Baron Gen3 radar provides superior bin-by-bin ground clutter suppression, in addition to optimally and dynamically adapting the process to the ground clutter environment. In fact, the need to continuously generate clutter maps is entirely eliminated.
CLEAN-AP™ technology helps make Baron Gen3 radar the optimal solution for radar site locations bordered by mountains, cities and other tall structures.
The CLEAN-AP™ trademark is owned by the Board of Regents of the University of Oklahoma
- Performs automated clutter detection and suppression with no need for manual intervention.
- The need for clutter maps is eliminated.
- Uses adaptive data windowing, achieving superior clutter suppression while maintaining data quality.
- CLEAN-AP™ is an integrated process providing a single algorithm for ground clutter detection and filtering on a bin-by-bin basis.
Proof of Performance
Huntsville Gen3 Testbed Results
No Need for Clutter Maps
In addition to its greatly increased accuracy, another advantage of CLEAN-AP™ is that it eliminates the need for static clutter maps to be generated. These maps require clear air conditions to be created, and cannot capture the effects of evolving ground clutter, such as anomalous propagation and seasonal changes in the surrounding flora. By dynamically determining the clutter contamination in each bin, CLEAN-AP™ removes the need to create these maps, freeing up time and operator manpower while improving accuracy.
Reflectivity from an evolving anomalous propagation event (left). Yellow bins (right) show areas where CLEAN-AP™ was applied, filtering out erroneous returns.
Adaptive Data Windowing
Traditional clutter filtering techniques apply the same data window to all radar imagery and measurements, regardless of the clutter environment. This has the tendency to either increase or reduce the amount of removed clutter, damaging the accuracy of the mixed signals containing meteorological targets and other non-targets like anomalous propagation, mountains, buildings and seasonal flora.
CLEAN-AP™ applies different data windows of varying aggressiveness based on the clutter target, removing the correct amount of clutter and preserving accuracy. The end result for the meteorologist is precise data, with local terrain accurately accommodated.
In this example, traditional ground clutter filtering is shown on the left; a radar sample is analyzed through only one data window. In the middle image, CLEAN-AP™ has used adaptive data windowing to identify areas of ground clutter caused by terrain, fauna and buildings. These undesirable returns are then removed from the display, as shown in the right image.
Want More Information?
Click here to read “Ground Clutter Mitigation for Weather Radars Using the Autocorrelation Spectral Density”, by Sebastian M. Torres and David A. Warde, Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma. Originally published in the October 14 issue of the American Meteorological Society Journal.