The structural health monitoring of a spacecraft product is an important process to ensure its safe and stable operation during launch and in orbit. Since multiple sensors will generate a large amount of data during long-term monitoring and require efficient transmission and storage, this article is aimed at data transmission problem puts forward and proves a fractional minimization model algorithm based on sparse recovery technology and an improved fractional screening algorithm, combined with satellite vibration test data and classic matching tracking algorithms for comparative analysis and verification. The comparison results show that, under the environmental conditions of the spacecraft, the relative error of data recovery obtained by the algorithm in this paper is lower than that of the two existing algorithms. The accuracy of data recovery is guaranteed under the condition of higher compression ratio, and hence we implement the data recovery from low-dimensional data to high-dimensional data transmission.