One of the most common methods of navigation data integration is the use of a Kalman filter. The paper presents a computer application facilitating testing of the properties of a Kalman filter, designed for a pedestrian or a robot positioning system using range measurements to several base stations. The description of the system is composed of a linear dynamics model and a non-linear observation model. Due to the non-linearity of the observation model, an extended Kalman filter (EKF) was chosen

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... for the position estimation. A computer application was developed in the MATLAB ® environment to test the filter properties and to support the process of choosing its parameters. The application gives an insight into the EKF operation and enables an assessment of its accuracy, depending on the assumed shape of the object trajectory, an assumed motion model, a number and locations of the base stations and the filter parameters. Chosen results of simulations are presented in the paper in the same form as they are seen in the GUI of our application. The application enables displaying the assumed trajectory of motion, its estimates from the EKF, as well as the components of estimated position and velocity errors. Additionally, it calculates and presents root-mean-squared (RMS) and maximal estimation errors. The application proved useful for testing the filter efficiency in various configurations. Due to its comfortable GUI, intuitive handling and wide range of possible tests, it can find its applications both in the research and the teaching.