As an analytical camera pose estimation algorithm, EPnP algorithm has attracted much attention in recent years for its low computational complexity. However, it is not robust to image noise. Hence, an iterative version of EPnP algorithm, called IEPnP, is proposed. The primary ideas of EPnP are preserved in IEPnP, 4 virtual control points are introduced, and their coordinates in the camera coordinate system are obtained through an initialization process based on weak perspective projection model. Gaussian-Newton algorithm is applied to optimize the coordinates of the virtual control points in the camera coordinate system. Finally, the pose estimation result is acquired by solving an absolute orientation problem. Meanwhile, the computational process is simplified in IEPnP. Simulations under different image noise levels are implemented, and the results show that IEPnP is more robust than EPnP to image noise while maintaining a high computational efficiency.