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Simultaneous quaternion estimation (quest) and bias determination
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Markley Sr., F. Landis |
| Copyright Year | 1989 |
| Description | Tests of a new method for the simultaneous estimation of spacecraft attitude and sensor biases, based on a quaternion estimation algorithm minimizing Wahba's loss function are presented. The new method is compared with a conventional batch least-squares differential correction algorithm. The estimates are based on data from strapdown gyros and star trackers, simulated with varying levels of Gaussian noise for both inertially-fixed and Earth-pointing reference attitudes. Both algorithms solve for the spacecraft attitude and the gyro drift rate biases. They converge to the same estimates at the same rate for inertially-fixed attitude, but the new algorithm converges more slowly than the differential correction for Earth-pointing attitude. The slower convergence of the new method for non-zero attitude rates is believed to be due to the use of an inadequate approximation for a partial derivative matrix. The new method requires about twice the computational effort of the differential correction. Improving the approximation for the partial derivative matrix in the new method is expected to improve its convergence at the cost of increased computational effort. |
| File Size | 660191 |
| Page Count | 14 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19900004101 |
| Archival Resource Key | ark:/13960/t1wd8rs92 |
| Language | English |
| Publisher Date | 1989-10-01 |
| Access Restriction | Open |
| Subject Keyword | Astrodynamics Bias Drift Instrumentation Estimates Attitude Inclination Algorithms Simulation Quaternions Least Squares Method Comparison Star Trackers Spacecraft Control Gyroscopes Matrices Mathematics Ntrs Nasa Technical Reports ServerĀ (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Article |