Abstract: Method for selecting a sea clutter training area in polarimetric synthetic aperture radar input data. A sea clutter reference distribution for a pixel magnitude value is provided. Based on the input data, one or more parameters of the reference distribution and a global covariance matrix are computed. The pixels are grouped into blocks. A block that minimizes a cost function is pre-selected, the cost function being derived from empirical moments of the block and moments of the reference distribution. A goodness-of-fit is computed for the pre-selected block with respect to the reference distribution. If the goodness-of-fit is sufficient, the block is selected as sea clutter training area. Otherwise, the steps of preselecting and computing a goodness of fit are repeated.

Abstract: Method for selecting a sea clutter training area in polarimet ric synthetic aperture radar input data. A sea clutter refer ence distribution for a pixel magnitude value is provided. Based on the input data, one or more parameters of the refer ence distribution and a global covariance matrix are computed. The pixels are grouped into blocks. A block that minimizes a cost function is pre-selected, the cost function being derived from empirical moments of the block and moments of the refer ence distribution. A goodness-of-fit is computed for the pre- selected block with respect to the reference distribution. If the goodness-of-fit is sufficient, the block is selected as sea clutter training area. Otherwise, the steps of preselect ing and computing a goodness of fit are repeated.