The problem of image reconstruction in the sparse system of radio frequency tomography with multiple scattering path is presented, and a self-adaptive sparse reconstruction method based on subspace tracking is proposed. The initial value and step length of the sparse degree are dynamically adjusted according to the characteristics of the target signal. And the attenuation coefficient of multipath linear model is sparse by using the subspace tracking algorithm. In the process of reconstruction, the supporting set is updated by the sparse estimation to reconstruct the target image. Compared with the other reconstruction algorithms, this method can effectively reduce the influence of the ghost on image definition and realize the clear reconstruction of tomography with unknown sparse. The reconstruction of the system and the probability of the ghost are presented. The experimental results show that the proposed algorithm can accurately estimate sparsity and the high precision image with low calculation amount, which can be used in other fields of radio frequency imaging.