TY - GEN
T1 - Spacecraft attitude and angular rate estimation from vector observations using real-time particle filtering
AU - Carmi, Avishy
AU - Oshman, Yaakov
PY - 2006/12/1
Y1 - 2006/12/1
N2 - A novel algorithm is presented for the estimation of spacecraft attitude and angular rate from vector observations. Belonging to the class of Monte Carlo sequential methods, the new estimator is a particle filter that uses approximate numerical representation techniques for performing the otherwise exact time propagation and measurement update of potentially non-Gaussian probability density functions in inherently nonlinear systems. The paper develops the filter and its implementation in the case of a low Earth orbit (LEO) spacecraft, acquiring noisy Geomagnetic field measurements via a three-axis magnetometer (TAM). The new estimator copes with the curse of dimensionality related to the particle filtering technique, by introducing innovative procedures that permit a significant reduction in the number of particles. This renders the new estimator highly efficient and enables its implementation with a remarkably small number of particles. The results of a simulation study are presented, in which the new filter is compared to a recently presented unscented Kaiman filter. The comparison demonstrates the viability and robustness of the new filter and its fast convergence rate.
AB - A novel algorithm is presented for the estimation of spacecraft attitude and angular rate from vector observations. Belonging to the class of Monte Carlo sequential methods, the new estimator is a particle filter that uses approximate numerical representation techniques for performing the otherwise exact time propagation and measurement update of potentially non-Gaussian probability density functions in inherently nonlinear systems. The paper develops the filter and its implementation in the case of a low Earth orbit (LEO) spacecraft, acquiring noisy Geomagnetic field measurements via a three-axis magnetometer (TAM). The new estimator copes with the curse of dimensionality related to the particle filtering technique, by introducing innovative procedures that permit a significant reduction in the number of particles. This renders the new estimator highly efficient and enables its implementation with a remarkably small number of particles. The results of a simulation study are presented, in which the new filter is compared to a recently presented unscented Kaiman filter. The comparison demonstrates the viability and robustness of the new filter and its fast convergence rate.
UR - http://www.scopus.com/inward/record.url?scp=84866904236&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84866904236
SN - 9781604235203
T3 - Technion Israel Institute of Technology - 46th Israel Annual Conference on Aerospace Sciences 2006
SP - 558
EP - 579
BT - Technion Israel Institute of Technology - 46th Israel Annual Conference on Aerospace Sciences 2006
T2 - 46th Israel Annual Conference on Aerospace Sciences 2006
Y2 - 1 March 2006 through 2 March 2006
ER -