In review, the literature of these phase-based methods for estimating soil moisture change can be divided into two major groups. One is the study of an experimental phenomenon, and the other is the research on scattering models. Gabriel et al. probably first found the link between the interferometric phase and the water in soil in 1989.4 However, the proposed explanation was based on the shrinking/swelling of clay soils. In 1998, Nesti et al. implemented an experiment in an anechoic chamber in the frequency band of 2 to 12 GHz, which revealed that the phase shift can be interpreted as the effect of the change of the dielectric properties of the surface soil.5 After that, Nolan et al., Hajnsek and Prats, S. Hensley et al., Morrison et al., Barrett et al., and Zwieback et al. investigated this technique further with the use of spaceborne, airborne, and ground-based SAR data, respectively.6–11 The scattering modeling on the relation between the interferometric phase and the dielectric constant of soil is very promising in its ability to analyze the influence and sensitivity of the system parameters on the soil moisture inversion. However, only a few studies concerning the scattering modeling of interferometric phase information for soil moisture applications could be found until recently. Oh et al. first developed the semiempirical relationship of the differential Mueller matrix for microwave backscattering from a bare surface.12 No soil moisture estimation method based on scattering models was developed from an interferometric phase until De Zan et al. in 2014.13 They proposed a model based on plane waves and the Born approximation, in which it is assumed that the backscatter is generated by a volume model under a flat surface. Then soil moisture values are obtained by minimizing the differences of coherence and phase triplets between the model predictions and L-band airborne SAR observations. The relation between the interferometric phase and soil moisture change is examined through comparison between the predicted and observed mismatches of the phase triplets. In this paper, we will insert the small perturbation method for a slightly rough surface assumption into the coherent scattering model and then present the phase relation of soil moisture values and system parameters, which can be directly utilized for soil moisture change detection. It can also be used for the occasions where the variations of coherence are small.