SIMULATION STUDY ON ESTIMATION METHOD OF SPECTRALLY PURE MATERIAL PROPORTION OF A SPACE TARGET BASED ON COST FUNCTION OPTIMIZATION

Abstract

A pure material proportion estimation method based on a spectral database is proposed. The method transforms the non-negative and linear constraints into a pure material proportional cost function minimization problem with a linear mixed model. The Newton algorithm is used to optimize the cost function, and the optimized extreme value is the optimal estimate of the proportion of pure material. Spectral simulation experiments are carried out for space target materials using the US Geological Survey database, and the experimental results show that the method proposed in this paper can help to estimate the proportion of pure substances in such targets quickly and accurately, especially when the number of mixed pure materials is large. Compared with some existing common algorithms, the proposed method is robust and can estimate the proportion of pure material in a space target when the signal-to-noise ratio is less than 40 dB. The accuracy of the method is 30% higher than that of the existing method.