To represent scattering polarization properties of painted surfaces, a multiple-component polarized bidirectional reflectance distribution function (BRDF) model is established on the basis of the Kubelka-Munk (KM) theory with the consideration of surface scattering and volume scattering. The model introduces the mirror parameter to characterize surface scattering contributions, and improves the traditional polarized BRDF model to make the new polarized BRDF model containing five parameters (real and imaginary parts of complex refractive index, surface roughness, relative diffuse reflectance coefficient, and mirror parameter) more consistent with the actual scattering polarization of painted surfaces. The degrees of polarization of black and green painted surfaces at different observation geometries are obtained by the outdoor experiment. The genetic algorithm is used to obtain key parameters based on measured data. The results show that the simulated results coincide with the experimental data for different painted surfaces, and the accuracy is improved by the introduction of mirror parameter. This work can be used as a basis for the extraction and effective identification of painted target polarization feature.