Ground-based synthetic aperture radar (GB-SAR) interferometry is a technique suitable for monitoring the movement and/or deformation of widespread targets remotely. The technique is capable of detecting a few tenths of millimeters. However, since the measurement is commonly carried out with a long-range distance, the influence of atmospheric condition can be a serious issue. A common and a practical way of correcting the influence on interferometric phase is based on coherent scatteres (CSs). In the present paper, a newly proposed method to detect CSs from measured data is discussed. The method detects CSs by taking the complex coherence of two SAR sub-images, which are formed from a data set. In order to form sub-images, the measured data are interleaved and SAR processing is applied respectively. An experimental demonstration showed that the method can successfully detect deployed corner reflectors as CSs. Furthermore, the movement of a target can accurately be measured when atmospheric correction based on CSs, which are detected by the proposed method. Since the method requires only data sets in the analyzing time period to detect CSs, the proposed method has an advantage in the real-time detection of target movements over a conventional method based on dispersion index, which requires number of data sets.