Most existing target acquisition (TA) models neglect the influence of background clutter, which results in inaccurate prediction of TA performance in a complicated environment. In this paper, all the background clutter is first quantitatively characterized by the distribution of edge clutter metric, and its effects on the target detection probability are analyzed. Further, a novel TA model is developed by combining this proposed clutter metric and the target task performance metric based on probability statistics theory. Moreover, this proposed model is validated by the search_2 dataset, and experiment results show that it is more consistent with the subjective detection probability than other models.