Application of UKF for MEMS IMUs and fluxgate sensors based attitude and heading reference system of carriers

In this paper, an unscented Kalman filter is designed towards a low cost solid-state attitude and heading reference system (AHRS). This system incorporates measurements from micro electronic mechanical system (MEMS) sensors, namely MEMS gyroscopes, MEMS accelerometers and MEMS fluxgate magnetometers, providing unaided, complete and accurate attitude and heading information for carriers. To realize the unscented Kalman filter (UKF) algorithm, the derived attitude parameterizations based on the direction cosine matrix (DCM) and quaternion algebra are intensively illustrated, an overall description of AHRS is presented in detail, and the state and measurement model are stressed by elaborate analyses as well. In addition, the superior performance of the UKF algorithm is discussed by the procedure of unscented transformation (UT) and unscented filter. The simulation test shows when the carrier is in dynamic environment, the attitudes and heading angles error are within 0.2 degrees and 2 degrees respectively. The particular filtering approach, illustrated here proves to be a practical approach for deriving body attitude and heading estimates in real time.