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A Statistical Approach to Mitigating Persistent Clutter in Radar Reflectivity Data

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4 Author(s)
Valliappa Lakshmanan ; University of Oklahoma, Norman ; Jian Zhang ; Kurt Hondl ; Carrie Langston

Although there are several effective signal processing methods for identifying and removing radar echoes due to ground clutter, the need to mitigate persistent clutter in radar moment data still exists if such techniques were not applied during data collection and the time series data are not available. A statistical approach to creating a clutter map from “found data”, i.e., data not specifically collected in clear air is described in this paper. Different methods of mitigating ground clutter are then compared using an information theory statistical approach and the best mitigation approach chosen. The technique described in this paper allows for the mitigation of persistent ground clutter returns in archived data where signal processing techniques have not been applied or have been conservatively applied. It is also helpful for correcting mobile radar data where the creation of a clear-air clutter map is impractical. Accordingly, the technique is demonstrated in each of the above situations.

Published in:

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  (Volume:5 ,  Issue: 2 )