Research on attitude updating algorithm based on modified Rodrigues parameters for low cost attitude and heading reference system

An all-attitude estimation algorithm for low cost attitude and heading reference system using extended Kalman filter based on modified Rodrigues parameters is designed. Aiming at the shortage of redundancy when using quaternion to describe attitude, modified Rodrigues parameters which are a three-dimensional independent vector are proposed for attitude representation. By switching between the modified Rodrigues parameters and their shadow parameters, the problem of singularity is solved. Considering the characteristics of the sensors of the system the estimation algorithm is established with gyroscope bias and modified Rodrigues parameters as state vector and the outputs of accelerometer and magnetometer as observation vectors, which is avoid the state error covariance matrix coming into being singularity. At last an all-attitude numerical simulation and an swing movement numerical simulation are used to demonstrate the efficacy of the algorithm.