Abstract: This paper introduces an a priori-embedded framework for the design of experiments and regional reconstruction in wind tunnel pressure testing for flight vehicles. We propose an experimental design methodology that integrates prior information, enabling a quantitative translation of prior knowledge to pressure design sites. This approach encompasses the extraction of features from prior pressure distributions, a clustering process for multiple scenarios, and an optimization strategy for the uniformity of triangular facets in the initial design. To capture variations in local pressure distributions, we introduce a proper orthogonal decomposition (POD)-based reconstruction technique that aligns the number of base modal shapes with the number of design sites. Evaluations on a typical high-speed aircraft demonstrate a mean reconstruction error of less than 0.2%, a root mean square error below 4%, and a maximum error not exceeding 30%. The consistent reconstruction performance across various cases is significant for the accurate determination of the lift curve slope. The incorporation of a priori-embedded design further refines the maximum error reduction by 0～10%. The framework requires only numerical outcomes and minimal empirical parameters, rendering it well-suited for complex configuration flight vehicles in pressure measurement testing.