Attitude determination with UD implementation of decoupled bias estimation

Abstract

The application of the UD implementation decoupled bias estimation to attitude determination is analyzed here. The advantage of decoupled bias estimation in general is the reduction in the dimensions of the filter and the subsequent reduction in the amount of processing. The purpose of the UD implementation is to mitigate the effects of round-off errors. A unique advantage of the application of decoupled bias estimation to attitude determination is that the bias processing can easily be turned off whenever a reconfiguration to a bias-free estimator mode is necessary. A comparison of the attitude error of the UD decoupled Kalman filter attitude uncertainty is given with respect to the coupled Kalman filter attitude uncertainty during the time periods when the bias processing is turned off. A detailed discussion of the UD implementation is given.

Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown Input

“…The well-known Kalman filter is optimal given a linear Gaussian model, but its performance will deteriorate in the presence of unknown biases, such as the unknown and time-varying delays in chemical processes [ 1 , 2 , 3 , 4 ], faults or failures in fault-tolerant diagnosis and control systems [ 5 , 6 ], registration errors in multi-sensor fusion [ 7 , 8 , 9 , 10 ], or inertial drift in navigation [ 11 , 12 , 13 , 14 ]. In general, such a bias is represented as an unknown input (UI) to the nominal model.…”

Compensation for Periodic Star Sensor Measurement Error on Satellite

“…However, the payload attitude measurement is often unavailable for attitude control system (ACS) engineers. Other relevant works are reported in [13][14][15][16][17][18].…”