  This paper considers a scenario of pursuing a moving target that may switch
behaviors due to external factors in a dynamic environment by motion estimation
using visual sensors. First, we present an improved Visual Motion Observer with
switched Gaussian Process models for an extended class of target motion
profiles. We then propose a pursuit control law with an online method to
estimate the switching behavior of the target by the GP model uncertainty.
Next, we prove ultimate boundedness of the control and estimation errors for
the switch in target behavior with high probability. Finally, a Digital Twin
simulation demonstrates the effectiveness of the proposed switching estimation
and control law to prove applicability to real world scenarios.
