Radar Simulations have become an essential tool in radar algorithm development and testing due to the lack of available high-resolution radar datasets and enormous difficulty in acquiring real-world data. However, simulating radar data is challenging as existing radar simulation tools are not easily accessible, require detailed mesh inputs and take hours to simulate. To address these issues, we present SHENRON, an open-source framework that efficiently simulates high-fidelity MIMO radar data using only lidar point cloud and camera images. We show that with SHENRON, one can generate simulated data that can be used to evaluate algorithms as effectively as on real data. Further, one can perform quick iterations through a vast parameter space of the radar to find the best set of parameters for any application, significantly aiding research in radar perception and sensor fusion.