This article presents a practical assessment of the recently developed state fusion method ellipsoidal intersection and focusses on distributed state estimation in sensor networks. It was already proven that this fusion method combines strong fundamental properties with attractive features in accuracy and computational requirements. However, these features were derived for linear processes with observability of the state vector in at least one of the local measurements. Therefore, several empirical case-studies are performed to assess ellipsoidal intersection with respect to three real-life limitations. A scenario of cooperative adaptive cruise control is used to analyze the absence of observability in any local measurement. Furthermore, the Van-der-Pol oscillator and a benchmark application of tracking shockwaves on highways assess the fusion method for nonlinear process models. The latter example is also used in a set-up where the employed state estimation methodology differs per node, so to meet different computational requirements per node.
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