Wavelength-resolution SAR change detection with constant false alarm rate

The paper introduces an incoherent change detection algorithm with constant false alarm rate (CFAR). The algorithm is based on a CFAR detector that preceded with an adaptive noise smoothing filter while the input of the filter is preliminary changes retrieved from a subtraction of surveillance SAR image to reference SAR image. The algorithm is tested with 24 data sets provided by CARABAS. The average probability of detection calculated for 1200 deployed vehicles is up to 96% while the false alarm rate calculated for an area of 288 square kilometers is only 0.15 per square kilometer. In our test, the algorithm did not require a longer processing time than other wavelength-resolution SAR change detection algorithms. Based on these evaluations, the introduced algorithm is seen to be effective.