| Summary: | 碩士 === 國立交通大學 === 機械工程學系 === 99 === This thesis aims to develop a sensor fusion system and implement it on a DSP platform. This sensor fusion system uses Extend Kakman filter to coordinate GPS output and IMU output to obtain accurate trajectory and attitude for an object in motion. The GPS can provide the position and velocity information. However, its data output rate is 1 Hz and the position accuracy is around 10 meter. The IMU, consisting of 3-axis accelerometers and 3-axis gyroscopes, can provide 3-axis accelerations and 3-axis angular rate measurements with a data rate around 1KHz. However, its signal is noisy and drifting. Therefore, it is preferred to combine these two sensors to obtain a high data-throughput and high accurate 6 DOF sensor fusion system.
The advantages of using Extended Kalman filter are that it can coordinate sensors with different data output rate and it can minimize the effect from measurement noise associated with each sensor. As for the signal drifting from IMU, this thesis discusses different sensor fusion systems that comprised of different sensor units. This research result is summarized in table shown in the conclusion section in this thesis.
Lastly, this thesis describes the detail procedures of sensor calibration which is needed prior to the construction of a sensor fusion system. This sensor fusion system will be implemented on a DSP platform. Currently, the GPS data, which is NMEA 0813 in ASCII codes, and the IMU data, which is analog, can feed in the DSP synchronously. The C-code coding for the Extended Kalman filter is on the way.
|
|---|
