Sequential multilayer fusion based assessment model for spacecraft launch success ratio

When assessing a spacecraft's launch success ratio (LSR), it is difficult to conduct many real flight tests before an actual mission because of the high costs, so various simulations must be used to comprehensively assess the LSR. However, during such simulations, problems can occur because the test data do not necessarily come from the same population, so the simulation samples may dominate the flight test samples. To overcome these issues, this paper proposes a sequential multilayer fusion based assessment model for spacecraft LSR. This model introduces an inheritance factor and an updating factor to correct the experimental simulation information, thus ensuring that the corrected information and the flight test information approximately obey the same population, which greatly reduces the influences of the different populations on the LSR. The sequential multilayer fusion model is an effective way to efficiently use prior information to obtain an accurate estimate. A numerical example illustrates how the proposed model can solve the problem of large sample data domination over small sample data and avoid the volatility effects of small flight test samples on the estimated LSR value.