A MEMS based, low cost GPS-aided INS for UAV motion sensing

This paper presents a new design and development of a low cost GPS (Global Positioning System)-aided INS (Inertial Navigation System) using Micro-ElectroMechanical-System (MEMS) inertial sensor. A typical MEMS type inertial sensor consists of three orthogonally aligned accelerometers and three orthogonally aligned gyroscopes confined in a very small chip. In this paper, the intensive preprocessing and modeling techniques of MEMS inertial sensor´s primitive, noisy motion data are outlined. These techniques transform the erroneous motion data into usable motion indicators illustrated in three-dimensional position, three-dimensional velocity, and three-dimensional orientation. GPS serves as an aiding device to tune the MEMS inertial sensor´s measurements through Kalman filter, while extra sensory feedbacks from magnetometers are employed to improve the system performance. Experiment was conducted to evaluate the performance of the GPS-aided INS by installing it into an Unmanned Aerial Vehicle (UAV) for motion sensing. Lastly, the experiment results are evaluated and verified using the motion data generated from a commercial navigation system.