Nautical measurements are randomly and systematically corrupted. There is a rich scope of knowledge regarding
the randomness shown by results of observations. The distribution of stochastic distortions remains an
estimate and is imprecise with respect to their parameters. Uncertainties can also occur through the subjective
assessment of each piece of available data. The ability to model and process all of the aforementioned items
through traditional approaches is rather limited. Moreover, the results of observations, the final outcome of
a quality evaluation, can be estimated prior to measurements being taken. This a posteriori analysis is impaired
and it is outside the scope of traditional, inaccurate data handling methods. To propose new solutions, one
should start with an alternative approach towards modelling doubtfulness. The following article focusses on
belief assignments that may benefit from the inclusion of uncertainty. It starts with a basic interval uncertainty
model. Then, assignments engaging fuzzy locations around nautical indications are discussed. This fragment
includes transformation from density functions to probability distributions of random errors. Diagrams of the
obtained conversions are included. The presentation concludes with a short description of a computer application
that implements the presented ideas.
