  We propose two distributed set-based observers using strip-based and
set-propagation approaches for linear discrete-time dynamical systems with
bounded modeling and measurement uncertainties. Both algorithms utilize a
set-based diffusion step, which decreases the estimation errors and the size of
estimated sets, and can be seen as a lightweight approach to achieve partial
consensus between the distributed estimated sets. Every node shares its
measurement with its neighbor in the measurement update step. In the diffusion
step, the neighbors intersect their estimated sets using our novel lightweight
zonotope intersection technique. A localization example demonstrates the
applicability of our algorithms.
