Attitude determination by combining arrays of MEMS accelerometers, gyros, and magnetometers via quaternion‐based complementary filter

In this study, an Attitude and Heading Reference System (AHRS) consisting of 5 modules is designed where each module has a triaxial gyroscope, accelerometer, and magnetometer. First, a method based on the Levenberg-Marquardt algorithm (LMA) is utilized to correct the bias error, scale factor and axes nonorthogonality. Also, the data from the 5 modules of AHRS are ensemble averaged to reduce the adverse effects of high-frequency noises. Then, the obtained trends are used in an orientation estimation algorithm based on a complementary filter algorithm. In this algorithm, the dynamical accelerations are first decreased via a low-pass filter. Afterwards, it is determined using an algorithm whether the system is experiencing magnetic distortion or not. If distortion is verified, magnetometers' data are discarded, as it will introduce noticeable error in estimating heading angle. In this case, the heading angle starts to diverge; however, employing 5 modules in the system decreases divergence rate noticeably, such that after 2 minutes in quasi-static conditions, the pitch, roll, and heading angles' errors decrease, respectively, from 36.195°, 23.201°, and 12.541° when only 1 module is used to 2.511°, 3.972°, and 0.984° when all 5 modules are used. Moreover, in dynamical conditions, these errors decrease from 37.916°, 13.633°, and 13.071° to 6.514°, 5.961°, and 0.284°. Once the distortion is removed from magnetic field, the magnetometers' data are used again to correct the heading error. The obtained results show that the root mean square (RMS) errors of pitch, roll, and heading angles in quasi-static conditions are 0.536°, 0.323°, and 0.601°, whereas in dynamical condition, they are 1.267°, 1.535°, and 0.994°, respectively.

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