When flow cytometry is used to analyze the polychromatic fluorescence of cells, multiple fluorescence spectra were often obtained, mixed with multicomponent fluorescence spectra. In this paper, the fluorescence spectra of cyanobacteria including many unknown fluorescence spectra were detected by flow cytometer with serious spectral overlap. In order to extract the main components and their concentrations from cyanobacteria spectra, a method of principal component analysis combined with multivariate curve resolution was used to process the fluorescence spectra of cyanobacteria. At first, the number of main components of cyanobacteria was given by principal component analysis, and then Evolving Factor Analysis was adopted to find the starting and end position of each component and to estimate the initial spectrum of pure components, finally Alternating Least Square combined with the pure components spectral unimodality and non-negativity was used to correct the initial estimation of pure components and concentrations. In the simulation and experiment, it was proved that the method could accurately estimate the number of pure components in the mixed spectra and fit the spectral peaks, and then accurately estimate the concentration of each component. This method can not only be applied in the spectral analysis of cyanobacteria, but also used for other multiple spectral mixture analysis.