To solve the poor robustness due to the changing moving target or the inaccurate tracking, a stratified sampling particle filter algorithm based on clustering method was proposed. The sampling space was divided into several parts by group sampling to make sampling points focused on the big probability density value part, thus the sampling error was reduced half of the original; the clustering algorithm could group the particles reasonably by weight, the diversity of particles was kept, thus the tracking precision was improved. The experimental results show that the tracking error of proposed method is less than half of the original one, and the stability has strengthened in each simulation time, as well as the tracking precision.

In a Distributed Virtual Environment (DVE) system running on Wide Area Network (WAN), the control effect of causal order consistency is determined by both the correctness of causality and the real-time due to the large network transmission delay. In order to achieve a better trade-off between the quality of causal order consistency and real-time in a DVE, a new dynamic causal order control approach was proposed. The core idea of this approach was to dynamically adjust and balance the amount of blocked effect messages and that of delayed causal messages on each site in a DVE system, so as to meet the demands of causality correctness and real-time requirement on message ordering delivery. The evaluation results demonstrate that the proposed approach can outperform the previous ones by effectively improving the quality of causal order control while simultaneously preserving the real-time property of DVE systems.