Highly quality soil moisture is significant for hydrological, meteorological and agricultural applications. At present, active and passive remote sensing are the only ways to monitor soil moisture directly at regional scale. However, the quality of single satellite-based soil moisture product is insufficient to meet the requirements of these applications. Hence, fusing these two soil moisture products to improve their quality of change capture ability and accuracy is a necessary and challenging work. This study proposes an improved double instrumental variable method to fuse active and passive soil moisture products. First, the method is improved in finding the best instrumental variables in time series based on correlation coefficient. Second, fused weights of input soil moisture products are estimated using the improved method. Finally, fused soil moisture products are obtained with higher change capture ability and higher accuracy. The Tibetan Plateau was selected as the study area to test the algorithm using both of the Climate Change Initiative (CCI) active and passive soil moisture products from the European Space Agency (ESA). The ground validation results show that, compared with the original soil moisture products, the change capture ability, expressed by the correlation coefficient (R), and the accuracy, expressed by the unbiased root mean square deviation (ubRMSD), have been both improved by about 10% on average. This study indicates that the proposed fusion method can effectively improve the quality of soil moisture products to further understand the global changing water cycle.