Further results on the observability analysis and observer design for single range localization in 3D
This work addresses localization challenges for autonomous vehicles or robotics in 3D environments, but it appears incremental as it builds on existing observability methods.
The paper tackled the problem of single range-based observability analysis and observer design for a 3D vehicle with constant unknown drift velocity, deriving necessary and sufficient observability conditions and enabling global state estimation using a standard Kalman filter.
The issue of single range based observability analysis and observer design for the kinematics model of a 3D vehicle subject to a constant unknown drift velocity is addressed. The proposed method departs from alternative solutions to the problem and leads to the definition of a linear time invariant state equation with a linear time varying output that can be used to globally solve the original nonlinear state estimation problem with a standard Kalman filter. Simple necessary and sufficient observability conditions are derived. Numerical simulation examples are described to illustrate the performance of the method.