  This paper develops new analytical process noise covariance models for both
absolute and relative spacecraft states. Process noise is always present when
propagating a spacecraft state due to dynamics modeling deficiencies.
Accurately modeling this noise is essential for sequential orbit determination
and improves satellite conjunction analysis. A common approach called state
noise compensation models process noise as zero-mean Gaussian white noise
accelerations. The resulting process noise covariance can be evaluated
numerically, which is computationally intensive, or through a widely used
analytical model that is restricted to an absolute Cartesian state and small
propagation intervals. Moreover, mathematically rigorous, analytical process
noise covariance models for relative spacecraft states are not currently
available. To address these limitations of the state of the art, new analytical
process noise covariance models are developed for state noise compensation for
both Cartesian and orbital element absolute state representations by leveraging
spacecraft relative dynamics models. Two frameworks are then presented for
modeling the process noise covariance of relative spacecraft states by assuming
either small or large interspacecraft separation. The presented techniques are
validated through numerical simulations.
