The Siamese network-based trackers are limited by the inherent tracking mechanism and search area selection mechanism of the Siamese network tracking framework. When the object is under challenging scenarios such as occlusion, fast motion, and out-of-view, how to perform stable and obust object tracking is always an urgent problem for Siamese trackers. To this end, in this paper, an object-tracking algorithm that combines the Siamese region proposal network with the global optical flow (GOF-SiamRPN) is proposed. By assisting the motion trend information of the object with global optical flow, the proposed method could effectively solve the potential tracking issues in these challenging scenarios. Extensive experimental results on VOT2019 and UAV123 show that the proposed method achieves a performance gain of 2.0% and 1.8% compared with the baseline method. It also achieves a competing performance compared to other state-of-the-art trackers.