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Position and orientation estimation using Kalman filtering and particle diltering with one IMU and one position sensor

In this paper, a novel position and orientation estimation method that relies on Kalman filtering and particle filtering is proposed. The orientation calculation error by using gyros increases over time due to the integration of angular velocity measurement errors. This paper describes how to estimate the orientation and position with a high accuracy when one inertial measurement unit (IMU) and one position sensor are available. The proposed filter takes advantage of the particle filtering component to estimate the orientation, and the Kalman filtering component to estimate the position of each orientation particle. The simulation results of the orientation calculation with no filter, with a Kalman filter (KF), and with the proposed filter are compared and discussed. The proposed filter is proven to reduce the position error and the rotation matrix error significantly.