In UAV aerial photography scenes, lighting changes, image blur, low resolution and other factors have a great impact on tracking performance, and previous target tracking algorithms mainly studied robust tracking under sufficient light and high resolution. This article proposes an adaptive image enhancement algorithm for unmanned aerial vehicle target tracking, which achieves robust tracking of unmanned aerial vehicles under dark changes in lighting and insufficient lighting. Firstly, an adaptive image enhancement module is constructed to identify the dark light scene and compensate for the corresponding image brightness and image contrast. Secondly, a dynamic constraint strategy is added to constrain the difference in tracking response, enabling the tracker to achieve time adaptation. Finally, experiments on two UAV benchmarks have proven the superiority of our method compared to other nine state-of-the-art trackers.