Regularized Robust Indirect Kalman Filter for Attitude Estimation
Mundla Narasimhappa, Arun D. Mahindrakar, Indian Institute of Technology-Madras, India; Marco H. Terra, University of Sao Paulo, Brazil; Samrat L. Sabat, University of Hyderabad, India
Low-cost MEMS based Inertial Measurement Unit (IMU) is a core device to Attitude Heading Reference System (AHRS). In general, IMU comprising three axis accelerometers and gyroscopes which can provide the position and attitude information of a vehicle in various application. In this paper, we propose a regularized robust Indirect Kalman filter (RRIKF) for attitude estimation when MEMS IMU subject to uncertainties. In addition, the quaternion is used for formulating a rigid body model. For the established attitude estimation model, a RRIKF algorithm is detailedly designed. Experimental results revealed that the proposed method is superior to the existing methods, in terms of both efficiency and accuracy.