Clutter removal in millimeter wave GB-SAR images using OTSU’s thresholding method

In this study, a filtering method based on the threshold value of normalized synthetic aperture radar (SAR) data is proposed to eliminate clutter in millimeter wave ground based synthetic aperture radar (GB-SAR) images. In the proposed method, first, stepped frequency continuous wave SAR data are reconstructed by using the back-projection algorithm and focused complex SAR data are obtained. Then, the amplitude values of the complex SAR data are normalized and the best threshold values to distinguish the target from clutter is determined by the OTSU’s thresholding method. Next, a filter mask is created that cancels all data below the computed threshold values. The mask matrix is finally multiplied with the resulted GB-SAR data to eliminate all clutter from the image. With the proposed technique, the best threshold value is determined automatically by directly processing the raw data without converting the SAR data into any RGB images. The proposed technique is validated through real GB-SAR experiments that were carried out in the frequency band of 78-81 GHz. In the experiments, challenging GB-SAR data are obtained using high cluttered background materials, and very successful filtering operations are performed with the proposed technique.