  Distance estimation plays an important role for path planning and collision
avoidance of swarm UAVs. However, the lack of annotated data seriously hinders
the related studies. In this work, we build and present a UAVDE dataset for UAV
distance estimation, in which distance between two UAVs is obtained by UWB
sensors. During experiments, we surprisingly observe that the stereo
triangulation cannot stand for UAV scenes. The core reason is the position
deviation issue due to long shooting distance and camera vibration, which is
common in UAV scenes. To tackle this issue, we propose a novel position
correction module, which can directly predict the offset between the observed
positions and the actual ones and then perform compensation in stereo
triangulation calculation. Besides, to further boost performance on hard
samples, we propose a dynamic iterative correction mechanism, which is composed
of multiple stacked PCMs and a gating mechanism to adaptively determine whether
further correction is required according to the difficulty of data samples. We
conduct extensive experiments on UAVDE, and our method can achieve a
significant performance improvement over a strong baseline (by reducing the
relative difference from 49.4% to 9.8%), which demonstrates its effectiveness
and superiority. The code and dataset are available at
https://github.com/duanyuan13/PCM.
