The radar is an example of a navigational device which enables monitoring of the sea areas. As every technical device, it is characterized by a certain limited level of functionality and reliability. Arranging observation stations so that plausibility of detecting any object at any place is greater than the threshold value is an operational research task. Formulation of the problem and the methods for solving it are presented in the paper

In traditional approach to position fixing navigator exploits mathematical apparatus based on probability theory. Series of assumptions are required in order to use the platform to draw final conclusions. Limited ability is available regarding fix accuracy a posteriori evaluation. In the paper Mathematical Theory of Evidence is exploited in order to introduce new foundations enabling modeling and solving problems with uncertainty. Modified scheme of approach towards making the fix delivers new standpoint for perceiving accuracy of the result

Separation schemes along with Vessel Traffic Services have improved the safety of navigation, particularly within restricted waters. Their role is rather passive and com-mon sense is still required whenever a decision is to be made. It is assumed that it could be beneficial in terms of collision or accident risk reduction once active measures are introduced. The concept raises a wide variety of problems that are to be discussed, de-fined and solved.

In most problems encountered in navigation, imprecision and uncertainty dominate. Methods of their processing rely on rather obsolete formalisms based on probability and statistics. Available solutions exploit a limited amount of available data, and knowledge is necessary to interpret the achieved results. Profound a posteriori analysis is rather limited; thus, the informative context of solutions is rather poor. Including knowledge in a nautical data processing scheme is impossible. Remaining stuck with the traditional formal apparatus, based on probability theory, one cannot improve the informative context of obtained results. Traditional approaches toward solving problems require assumptions imposed by the probabilistic model that exclude possibility of modelling uncertainty. It should be noticed that the flexibility of exploited formalism decide the quality of upgrading models and, subsequently, on the universality of the final results. Therefore, extension of the available formalisms is a challenge to be met. Many publications devoted to the mathematical theory of evidence (MTE) and its adaptation for nautical science in order to support decision making in navigational processes have enabled one to submit and defend the following proposition. Many practical problems related to navigational ship conducting and to feature uncertainty can be solved with MTE; the informative context of the obtained results is richer when compared to those acquired by traditional methods. Additionally, a posteriori analysis is an inherent feature of the new foundations. The brief characteristics of a series of publications devoted to the new methodology are the main topics of this paper.

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.