Realization of Low-Cost IMU/GPS Integrated Navigation System

The paper focuses on the IMU (inertial measurement unit)/GPS (Global Position System) integrated navigation system data processing methods. Firstly, the EMU error equations in the Earth fixed coordinates are introduced. Then, a fading Kalman filter is simply introduced and its shortcomings are analyzed. Further, an adaptive filter is applied in low-cost IMU/GPS integrated navigation system, in which the adaptive factor is constructed based on the predicted residuals. Finally, a practical example is given. The results have shown that the adaptive filter is valid and reliable when applied in IMU/GPS integrated navigation system

I. Introduction

IMU (Inertial Measurement Unit) is a kind of sensor sensing angle rate and acceleration. Micro- Electro-Mechanical System (MEMS) is the integration of mechanical elements, sensors, actuators, and electronics. IMU errors come from inside the unit, and the errors accumulate through time. This is the reason why IMU can't meet the requirement of navigation and positioning in accuracy alone. IMU/GPS integrated systems, however, benefit with their own advantages, and perform higher efficiently with the mutual benefit. It is well known that there are two kinds of IMU/GPS, i.e., loosely and tightly integrated systems [3], [8], the former has lower accuracy, but is simple and easy to realize.