Colored-Noise Kalman Filter for Vibration Mitigation of Position/Attitude Estimation Systems

A colored-noise Kalman filter is designed to diminish the error effects caused by sensors placed on vibrating structures. This paper deals with sensors that are used to estimate position, attitude or both. Here we focus on a vision-based system, which uses a set of lightemitting diode beacons with a focal plane detector to determine line-of-sight measurements. Estimation of both position and attitude is possible with this system. Vibrational effects are added to the beacon locations and a colored-noise filter is designed to mitigate the effects of the beacon movements on state estimation. A sensitivity study is conducted for this paper work, where the effects of beacon location errors on the estimation of a vehicle’s position and attitude are examined. Beacon location variation is introduced into the standard vision-based navigation problem as second-order vibration noise. Further, an error in the process-noise covariance is assumed and its effect on the estimated quantity is observed. Different magnitudes of vibration are added to the beacons position and the robustness properties of the colored-noise filter is analyzed. Results indicate that the colored-noise filter provides significant improvements over a filter that does not account for vibrational effects.