Fine gratings with spatial periods below one micron, either ruled mechanically or patterned holographically, play a key role as encoders in high precision translational or rotational coordinate or measuring machines. Besides, the fast in-line characterization of submicron patterns is a stringent demand in recent microelectronic technology. Thus, a rapid, destruction free and highly accurate measuring technique is required to ensure the quality during manufacturing and for final testing. We propose an optical method which was already successfully introduced in semiconductor industry. Here, the inverse scatter problem inherent in this diffraction based approach is overcome by sophisticated data analysis such as multivariate regression or neural networks. Shortly sketched, the procedure is as follows: certain diffraction efficiencies are measured with an optical angle resolved scatterometer and assigned to a number of profile parameters via data analysis (prediction). Before, the specific measuring model has to be calibrated. If the wavelength-to-period rate is well below unity, it is quite easy to gather enough diffraction orders. However, for gratings with spatial periods being smaller than the probing wavelength, merely the specular reflex will propagate for perpendicular incidence (zero order grating). Consequently, it is virtually impossible to perform a regression analysis. A proper mean to tackle this bottleneck is to record the zero-order reflex as a function of the incident angle. In this paper, the measurement of submicron gratings is discussed with the examples of 0.8, 1.0 and 1.4 micron period resist gratings on silicon, etched silicon oxide on silicon (same periods) and a 512 nm pitch chromium grating on quartz. Using a He-Ne laser with 633 nm wavelength and measuring the direct reflex in both linear polarizations, it is shown that even submicron patterning processes can be monitored and the resulting profiles with linewidths below a half micron can be characterized reliably with 2(theta) - scatterometry.