Recursive depth parametrization of monocular visual navigation: Observability analysis and performance evaluation

In this paper, the theoretical and practical feasibility of estimating ego-motion in monocular navigation is under investigation. In particular, this paper concerns the observability issues of monocular navigation models. In order to recover the ego-motion of the monocular camera from 2D (two-dimension) image sequence, this paper proposes a novel recursive parametric model. This model differs from other traditional parametric models with the reduced state-dimension and the consistent observability of system state. In addition, the consistent observability of different models are compared by using time-varying observability analysis theory. At the end of this paper, two groups of experiments are implemented to validate the effectiveness of the proposed method.