In this paper, we focus on the problem of micro aerial vehicle’s (MAV’s) localization in unknown, GPS-denied indoor condition. For this problem, we present a system to obtain the pose estimation and the occupancy grid map of the environment by using laser range finder. In addition, to improve the accuracy and robustness of tracking algorithm, we design a method by fusing the pose estimation from SLAM with IMU data. Furthermore, because of the length of the corridor may exceed the measurement range of the laser range finder, we specifically put forward an approach by fusing optical flow and IMU to compensate the error for this. Plenty of real flights and static precision experiments have proved the validity and accuracy of the proposed method.