The modulation signal of inverse synthetic aperture lidar(ISAL) has the characteristics of high frequency and wide bandwidth, making traditional “stop and go” model of inverse synthetic aperture radar unavailable. By establishing accurate imaging model for ISAL, translational error, rotational error, and model error existed in ISAL image formation process are analyzed. When applying translational compensation and rotational compensation separately to traditional ISAL, the residual error existed in translational motion compensation influences the precision of subsequent rotational motion compensation. Jointly compensated imaging algorithm based on the Nelder-Mead simplex method and the quasi-Newton method is proposed. The proposed algorithm iteratively searches for motion parameters of the target based on the Nelder-Mead simplex method, the obtained optimal solution is used as the motion compensation term to eliminate three kinds of errors globally. Then the quasi-Newton method is applied for removing the residual error. Simulation results show that compared with the traditional separate compensation algorithm, the proposed algorithm can estimate motion parameters of target accurately and obtain a better quality of ISAL image.