A robust and data-dependent adaptive thresholding algorithm for nonhomogeneity detection in non-Gaussian interference is addressed. The algorithm is to be used as a preprocessing technique to select a set of homogeneous data from a bulk of nonhomogeneous compound-Gaussian secondary data employed for adaptive radar. An iterative version of the algorithm is also suggested in situations of multiple outliers in the secondary data. Performance analysis is conducted with simulated data as well as with real sea clutter data.