Design, Modelling and Simulation of Integrated Gyro-Free IMU and an Aiding Navigation System by Applying Extended Kalman Filter in ECEF Frame

This paper addresses a novel gyro-free inertial measurement unit (IMU) structure and a new method for data fusion by integrating a gyro-free IMU and an auxiliary navigation system by applying extended Kalman filter. IMU is applied to navigate and determine the position, velocity and attitude of moving vehicles. Because of simpler manufacturing, lower cost, smaller size and less energy consumption of accelerometers in contrast to gyros, gyro-free IMUs are used in some navigation applications. The first step is to propose an asymmetric structure for six accelerometers and their equations. The complete determination of linear accelerations and angular velocities of moving vehicles can be achieved through the use of this structure. The proposed structure has some merits in comparison with similar works in this field such as a smaller number of accelerometers and simplicity of extracted equations. Then, for improving the accuracy and performance of the proposed IMU, an aiding navigation system called GPS, is integrated with the proposed non-gyro system. Extended Kalman filter is the main tool for data fusion and is used to integrate these systems. Finally, simulations are provided to illustrate the effectiveness of the proposed algorithm for integrating a gyro free IMU and a GPS.