Kalman-filtering-based angular velocity estimation using infrared attitude information of spacecraft

We study the problem of estimating the spacecraft attitude angular velocity using the signal of the spacecraft attitude angular sen- sors such as the IR horizon sensor, the star sensor, and the full attitude global positioning systems (GPS) sensor for the first time. A signal state model is established. Based on the linear least mean squares (LMS) error criterion, recursive Kalman filtering is developed for the direct esti- mation of angular velocity. Our algorithm requires relatively few compu- tations and relatively small storage quantities. Finally, the new algorithm is applied to a set of physical simulated IR data, and the results have the advantages of smaller time lag, higher accuracy, and perfect smooth- ness. © 2000 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(00)00702-9)