The article is devoted to the research of methods of processing of navigation information. To collect experimental navigation information, a system based on the Real time locating system was used, which includes 9 receivers and one label. Label positioning takes place by measuring the distance from the label to the receivers (at least 3). Measurements were made at 9 points on the test polygon to determine the point with the highest standard deviation (STD). However, there is no relationship between the position of the point and the STD. As a result, data sets of navigational information were received, which are subject to further processing. The standard deviation of the navigation system is calculated. The methods of linear filtration are studied: a median filter, a moving average filter and a Wiener filter. Their effectiveness was assessed from the point of view of the reduction of STD. The algorithms of each of the filters are presented. Shown are graphs showing the smoothing properties of the filters. The general properties of the pros and cons of each filter are given. The STD is calculated after applying different filters. Conclusions are given about the most effective filter from the point of view of the STD. It turned out to be a moving average filter. However, the decrease in STD was not significant. Conclusions are drawn about the need to integrate navigation information from various sources.

Keywords: navigation, positioning, data filter, linear filter, moving average filter, median filter, Wiener filter, mobile objects control, navigation information processing, standard deviation