Analytical Constrains for Performance Improvement of the Integration INS/GNSS into Navigation System

The integration of Inertial Navigation System (INS) into Global Navigation Satellite System (GNSS) utilizing Inertial Measurement Unit (IMU) has become increasingly common in Mobile Mapping Systems (MMS) and navigation. It enables the accurate determination of the location, velocity, and attitude of mobile entites in a seamless manner. Besides, thanks to advantages such as compact light weight structures, low cost and energy consumption, the Micro-Electro-Mechanical System (MEMS) IMU and GPS transceivers have been an active research area. However, the quality of the small-cost INS/GPS systems remains low, specially in GNSS-noise and without-GNSS environments. To improve the system performance, this study applies analytical constraints, consisting of non-holonomic constraints and zero-velocity updates, to the data unification, such as the Enhanced Kalman Filter. Experiments and data analysis are used to validate the benefits of our proposal.