Being lost, object redetection is a crucial step for retracking object for long time visually, but due to background interference and the introduction of numerous similar objects, and the performance of re-detection is poor, for this reason, a method of redetecting object is proposed based on dual modulation. First, a modulator with search frame feature is designed to enhance the correlation between search frame features and the target, thereby improving the capability of the re-detection method to handle complex background interference. Secondly, a method with proposal features is designed to enhance the response of proposal features to the target, thereby improving the capability of the re-detection method to handle interference from similar objects. In order to verify the effectiveness of the method proposed in this paper, TransT and ToMP are selected as the base trackers in combination with the algorithms proposed in this pa per form two long-term visual tracking algorithms, and the experiments are carried out on four datasets, i.e. UAV20L, LaSOT, VOT2018LT, and VOT2020LT. The experimental results show that the proposed method significantly improves the long-term tracking performance of the mentioned-above two basic trackers.