Optimization method of MEMS IMU/LADAR integrated navigation system based on Compressed-EKF

Micro-electromechanical Systems (MEMS) IMU/ LADAR integrated navigation is a new-type autonomous navigation and environment detection method. It has a broad application prospect in the indoor environment. In MEMS IMU/LADAR integrated navigation system, the MEMS inertial sensors are used to measure vehicle movement. The LADAR is used to detect environmental features, and their outputs are fused by a digital filter, to provide precise position and environment mapping information for small rotorcraft. However, with the increasing amounts of observed landmarks, the computation complexity of traditional Extended Kalman Filter (EKF) increase excessively, making it unable to meet the realtime navigation requirement for small rotorcraft. In addition, the existing LADAR is generally planar scanning radar. When the aircraft's attitudes change, there is no guarantee that detecting plane maintains in a horizontal plane. This makes detecting information couple attitude angle measurement errors, and would bring great errors to the integrated navigation results. According to the problems mentioned above, the paper proposes the LADAR's attitude angle coupling error compensation algorithm. The navigation filter is designed based on Compressed-EKF(CEKF) algorithm. And the experimental prototype is designed for MEMS IMU/LADAR integrated navigation system, to verify CEKF algorithm in indoor environment. The tests show that the proposed algorithm can effectively improve the LADAR's precision and decrease the calculation amount of filtering algorithm. The research has significant reference value for small rotorcraft's simultaneous location and mapping (SLAM) technology in the structured indoor environment.