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Determining index of refraction of rough surface object is important for target identification and classification by polarization measurement, but it is difficult to directly acquire the imaginary part of complex refractive index. Many numerical inverse methods are proposed, which are Vimal-Milo method and improved Vimal-Milo inversion method. The first method is evaluated by P-G model, which is based on scalar bidirectional reflectance distribution function with a mode of “polarization ratio – angle correlation”. But this method is only applied in almost specular reflection and its defects are explicit in application. The second method named improved Vimal-Milo method is proposed based on the mode of ‘relative polarization component – angle correlation’. In this method, the inversion formula for the complex refraction index was semi-empirical deduced and global search algorithms such as genetic algorithm or Hooke – Jeeves search algorithm were used. Although two inversion methods are same based on P-G model, polarization measurement are different of which one is polarization ratio and the other is S1 component. The simulation results showed that (1) roughness parameters (correlation length and height standard variance of microfacet) have little effect to inversion of complex refraction index, and they must be calibrated accurately. (2) stokes values and reflection angle have smaller effect and they can be measured by polarimeter and angulometer. (3) incident angle is strongly correlated with complex refraction index and must be measured largely and precisely. (4) we must try to avoid poor specular reflection condition and improve degree of polarization.
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