The amount of the grain in bulk silos is the most important issue in commercial care. Therefore many level measurement methods have been used to measure the level of solids in silos. Existing methods, however, are generally based on one-point measurement which makes the three dimensional (3D) level measurement impractical. Microwave radar based systems can be used to 3D perception but the multiple scatterings occurred from metallic walls of the silo, makes it impossible. In this study we present the preliminary results of our compressive sensing based reconstruction algorithm to enhance backscattering signals inside a grain silo. The method proposed here eliminates the effect of multiple scattering form silo wall and gives the accurate reading of the grain level. The effectiveness of the recommend CS-based reconstruction method, which will be able to extend to 3D level perception, was verified through a real data of bulk silo.