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Vision-Based Relative State Estimation Using the Unscented Kalman Filter
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 Title & Authors
Vision-Based Relative State Estimation Using the Unscented Kalman Filter
Lee, Dae-Ro; Pernicka, Henry;
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A new approach for spacecraft absolute attitude estimation based on the unscented Kalman filter (UKF) is extended to relative attitude estimation and navigation. This approach for nonlinear systems has faster convergence than the approach based on the standard extended Kalman filter (EKF) even with inaccurate initial conditions in attitude estimation and navigation problems. The filter formulation employs measurements obtained from a vision sensor to provide multiple line(-) of(-) sight vectors from the spacecraft to another spacecraft. The line-of-sight measurements are coupled with gyro measurements and dynamic models in an UKF to determine relative attitude, position and gyro biases. A vector of generalized Rodrigues parameters is used to represent the local error-quaternion between two spacecraft. A multiplicative quaternion-error approach is derived from the local error-quaternion, which guarantees the maintenance of quaternion unit constraint in the filter. The scenario for bounded relative motion is selected to verify this extended application of the UKF. Simulation results show that the UKF is more robust than the EKF under realistic initial attitude and navigation error conditions.
Vision sensor;Unscented Kalman filter;Multiplicative quaternion error;Relative attitude;Relative position;
 Cited by
Vision-Based Spacecraft Relative Navigation Using Sparse-Grid Quadrature Filter, IEEE Transactions on Control Systems Technology, 2013, 21, 5, 1595  crossref(new windwow)
Visual Detection and Servoing for Automated Docking of Unmanned Spacecraft, TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, AEROSPACE TECHNOLOGY JAPAN, 2014, 12, APISAT-2013, a107  crossref(new windwow)
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