Feasibility of precipitable water vapor (PWV) retrieval from the ground-based infrared measurements in clear sky conditions was performed based on the radiative transfer simulation and retrieval experiments. The effects of aerosol, view zenith angle, and instrument spectral response function (SRF) on clear-sky infrared brightness temperature (T_sky) were analyzed. The results showed that atmospheric aerosol and SRF have obvious influence on T_sky measurements and PWV retrievals. The relationship between T_sky and PWV under low aerosol loading conditions is better than that of high aerosol loading conditions. Aerosol information is necessary for the inversion of high-precision PWV using a single-angle T_sky measurement. T_sky at the infrared atmospheric window (i.e., 10 to 12  μm) has a better exponential relationship with PWV than that covers 6.3  μm water vapor and 9.6  μm ozone absorption bands. Furthermore, a neural network (NN)-based PWV retrieval algorithm was proposed using dual-angle T_sky measurements and near-surface air temperature (T_air). The results showed that the introduction of multiangle T_sky can effectively reduce the influence of aerosol on PWV retrieval and improve the PWV retrieval accuracy. The determination coefficient, root-mean-square error, and bias of the NN model using dual-angle T_sky (i.e., 0 deg and 30 deg) and T_air were 0.989, 0.191, and 0.002 cm, respectively.