The detection of maneuvering weak targets by monostatic ground-based radar is a hot issue， and the detection performance of moving targets can be improved by increasing the accumulation time. However， with the increase of accumulation time， the movement of maneuvering target causes the phenomenon of range cell migration （RCM） and Doppler frequency migration （DFM）， which leads to the loss of accumulation gain. To solve this problem， a long-time accumulation method for weak maneuvering target detection in monostatic radar is proposed in this paper. The segmentation strategy is firstly given in the proposed method， then the motion compensation algorithm with the second-order keystone transform is used twice to correct the RCM， later LVD is used to estimate the motion parameters and the phase compensation is carried out. Finally， the detection probability and detection accuracy are further improved by sliding window non-coherent accumulation. The simulation results show that the detection performance of the proposed method is better than the traditional accumulation detection algorithm in the weak maneuvering target condition. The proposed method compensates for the gain loss caused by RCM and DFM and improves the signal-to-noise ratio of coherent and non-coherent accumulation gain. Furthermore， it can balance the computational complexity and accumulation gain at the same time.