Rice height, an important index of rice growth monitoring, is a comprehensive reflection of rice itself, soil, hydrology and meteorology. So accurate, efficient, and large-scale inversion of rice crop height can provide reliable basis for rice identification, phenological monitoring, pest and yield estimation. Synthetic Aperture Radar (SAR), because of its all-weather day-night imaging capability, has been proven to be one of the important means for inversion of rice height. Based on polarimetric SARinterferometry (PolInSAR), the inversion algorithm of scattering model has the characteristics of support of rigorous physical model and high inversion accuracy, which has become a hot spot of inversion of vegetation height. In this paper, based on PolInSAR technology, a new method based on Random Volume over Ground (RVoG) model for rice height inversion was proposed. The inversion experiment of rice height was carried out using the TanDEM-X PolInSAR data of 9 time phases in the rice growing season of 2015. First of all, 8 complex coherence coefficients were obtained based on PolInSAR data in each phase. and these were used for a product of decorrelation under the consideration of satellite dual-station mode. Then, the RVoG model was established for the characteristics of paddy fields. Moreover, using this model, an iterative algorithm of rice height inversion was constructed. Finally, the rice height inversion and precision evaluation using TanDEM-X data of 9 time phases were carried out. The results showedthat when rice height was higher than 0.4 m, a coefficient of determination (R2) of was 0.86 and RMSE was 6.69 cm. When rice height was low (rice height was less than 40 cm), inversion resultswith inversion error of 0.1～0.8 m were significantly overestimated. Through analysis, on the premise that TanDEM X data reflect volume scattering of rice plants well, the inversion algorithm of rice height based on RVOG model can invert the rice height between 0.33～1.2 m with high precision.