Abstract
Nonlinear filtering plays an important role in various space-related applications and especially in orbit determination and navigation problems. Differential algebraic techniques are here proposed as a valuable tool to reduce the computational burden of Monte Carlo based filtering algorithms, and in particular of the ensemble Kalman filter, without losing accuracy. The performance of the proposed filter is assessed on typical problems in spacecraft navigation. The cases of low estimation frequency and nonlinear measurements are also considered. Copyright© (2012) by the International Astronautical Federation.