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We describe a novel technique for vision-based UAV (unmanned aerial vehicle) navigation. In this technique, the navigation (position estimation) problem is formulated as a tracking problem and solved by a particle filter. The state and observation models of the particle filter are established based on a stereo analysis of the image sequence generated by the UAV's video camera in connection with a DEM (digital elevation map) of the area of the flight, which helps to control estimation error accumulation. The efficacy of this technique is demonstrated by simulation results.