Abstract:

The integration of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) is now widely used for navigation applications and Mobile Mapping System (MMS) to seamlessly determining position, velocity and attitude of the mobile platform. With low cost, small size, ligh weight, The Micro‐Electro‐Mechanical System (MEMS) IMU is now the trend in research and using for many applications. However, researchs in the literature indicated that the performance of the low cost MEMS IMU systems is still poor, particularly, in case of GNSS ‐ noise and ‐ denied environment. To overcome this problem, this research apply an analytic contraint called Non‐holonomic constraint in the data fusion engine such as Extended Kalman Filter to improve the performance of the system. The benefit of the proposed method will be demonstrated through experiments and data analysis