This paper considers the problem of tracking multiple acoustic sources in 3-D space using a distributed acoustic vector sensor array. Unlike the existing two-stage localization approach, which estimates the direction of arrival of the source at each sensor first and then triangulate a 3-D position, a particle filtering approach is developed to directly fuse the signals collected from distributed sensors. To enhance the tracking performance and constrain the computational complexity, an information filter is developed to approximate the optimal importance sampling. Since the position state of the source is linear with the velocity state, a Rao–Blackwellization step is employed to marginalize out the velocity component. In addition, the posterior Cramér–Rao bound is developed to provide a lower performance bound for the distributed tracking system. Both the numerical study and simulations show that the proposed tracking approach significantly outperforms the two-stage localization approaches for 3-D position estimation.