An ANN embedded POS algorithm for a low cost MEMS INS/GPS integrated system

Digital mobile mapping, the methodology that integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. Direct geo-referencing is the determination of the time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning by GPS and inertial navigation using an IMU. They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. KF (Kalman Filter) has been considered as the optimal estimation tool for real-time INS/GPS integrated kinematic position and orientation determination. An intelligent and hybrid scheme consists of an ANN and KF. It had been proposed to overcome the limitations of the KF and improve the performance of an INS/GPS integrated system successfully in the previous study. However, the accuracy requirements of general mobile mapping applications can not be achieved easily even by the use of the ANN-KF scheme. Therefore, this study proposes an intelligent POS to improve the overall accuracy of position and orientation parameters for a MEMS INS/GPS integrated system to the next level in a post-mission mode. Combining the MEMS INS/GPS integrated system and intelligent POS scheme proposed in this study, a cheaper but reasonably accurate POS can be anticipated.