This paper considers an approach to solving the problem of unmanned vehicle self-positioning in motion. The main method of improving the performance of navigation systems and reducing the probability of false alarm is sensor data duplicating and merging them for further integrated processing. However, this method has a significant disadvantage of “fixing” the priority sensor when reconciling data from heterogeneous sensor systems. Ignoring current environmental conditions may result in transmitting false data to a navigation system by the sensor being set as the priority one; and these data will be considered by the system as the only valid ones. In this regard, the authors propose an algorithmic approach for merging data from heterogeneous sensors, taking into account changes in the hierarchy of incoming measurement information depending on external environment conditions.