This work analyzes unobservable directions of Vision-aided Inertial
Navigation System (VINS) and Lidar-aided Inertial Navigation System (LINS)
nonlinear model. Under the assumption that there exist two features observed by
the camera without occlusion, the unobservable directions of VINS are uniformly
globally translation and global rotations about the gravity vector. The
unobservable directions of LINS are same as VINS, while only one feature need
to be observed. Also, a constraint in Observability-Constrained VINS (OC-VINS)
is proved