Abstract

In single-shot laser radar speckle noise, drop-outs, outliers, and eventually, non-cooperative targets are to be considered in order to ensure high accuracy and reliability of measurement data. The most common approach for the stabilization of laser radar data is temporal averaging over several shots. This, however, is not in all cases the best method for the reconstruction of noisy imagery data. It is shown that principal-component filtering can yield a remarkable improvement of accuracy and robustness of range data.

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