Paired comparison is a frequently used method in psychophysical studies. However, with the increase of the number of the stimuli, the number of comparisons increases exponentially. Square design is one of the balanced sub-set paired comparison methods which could reduce the number of comparisons while producing comparably precise results under some assumptions. However, when there are observation errors from observers' attentiveness, the square design would produce large estimation errors. Thus, an improved square design which is robust to observation errors is proposed. Using a Monte Carlo simulation, the proposed method is evaluated and shows improvement in efficiency. The original design is applied in a visual discomfort subjective test of 3DTV. In addition, both of the two designs are studied by utilizing our previous full comparison data. The test results showed that the proposed improved square design is more robust to observation errors. Another important finding is that the influence of the occurrence of some other stimuli on voting is significant. Whether the proposed method could reduce the prediction errors induced by it is still under study.