Three-dimensional optical coherence tomography (OCT) is a new ophthalmic imaging technique offering more detailed quantitative analysis of the retinal structure. Eye movement during 3D OCT scanning, however, creates significant spatial distortions that may adversely affect image interpretation and analysis. Current software solutions must use additional reference images or B-scans to correct eye movement in a certain direction. The proposed particle filtering algorithm is an independent 3D alignment approach, which does not rely on any reference image. 3D OCT data is considered as a dynamic system, while location of A-scan is represented by the state space. A particle set is generated to approximate the probability density of the state. The state of the system is updated frame by frame to detect A-scan movement. Seventy-four 3D OCT images with eye movement were tested and subjectively evaluated by comparing them with the original images. All the images were improved after zalignment, while 81.1% images were improved after xalignment. The proposed algorithm is an efficient way to align 3D OCT volume data and correct the eye movement without using references.