Under-sampled non-Cartesian trajectories play a vital role in accelerating MRI scan time; however, the solution image may have aliasing artifacts. In this work, a GROG gridding based Sparse-SENSE reconstruction is presented to get the solution image from the non-Cartesian under-sampled radial MR data. The proposed method is tested on 1.5T human head data at different acceleration factors (i.e. 4, 6 and 9) and compared with pseudo-Cartesian GRAPPA scheme. The results show that the proposed method provides significant improvement (e.g. 87% improvement in AP at AF=4) in the reconstructed images as compared to conventional pseudo-Cartesian GRAPPA reconstruction.