This work presents a novel target-free extrinsic calibration algorithm for a 3D Lidar and an IMU pair using an Extended Kalman Filter (EKF) which exploits the \textit{motion based calibration constraint} for state update. The steps include, data collection by motion excitation of the Lidar Inertial Sensor suite along all degrees of freedom, determination of the inter sensor rotation by using rotational component of the aforementioned \textit{motion based calibration constraint} in a least squares optimization framework, and finally, the determination of inter sensor translation using the \textit{motion based calibration constraint} for state update in an Extended Kalman Filter (EKF) framework. We experimentally validate our method using data collected in our lab and open-source (https://github.com/unmannedlab/imu_lidar_calibration) our contribution for the robotics research community.