The dependence of modern warfare on missiles continues to increase, and scientific analysis of the influencing factors of missile misses is of great significance for improving the accuracy of missile hits. With the continuous development of new technologies such as cloud computing, edge computing, Internet of Things and big data mining, especially the implementation of digital twin technology in various industries. This article attempts to use digital twin technology to study the key factors affecting missile misses. First, build a digital twin model of the missile based on the concept of cloud-side collaborative computing. Realize the data collection of the missile physical entity, edge-side data over-limit judgment, and cloud miss-target diagnosis and analysis on the three levels of “cloud-side-end”, thereby completing the mapping and data interaction between the missile physical entity and the cloud digital twin model. At the same time, the degree, tightness and betweenness of nodes in the undirected graph can be used to quantitatively calculate the influence of each over-limit parameter on the missile’s missed target, so as to obtain key parameters and parameter combinations. Finally, taking the XX anti-tank missile as an example, the feasibility and effectiveness of the proposed method are verified.