Nonlinear wave propagation is observed in the noise created by many sources such as fighter jet aircraft, explosions, gun fire, sonic booms etc. The wave acquires nonlinearity which becomes more pronounced with distance when the fluctuations in the state variables are high enough when compared with the ambient values. This paper describes a frequency domain algorithm to predict nonlinear noise propagation. The propagation of the sound generated by high-speed jets, as mentioned, experiences nonlinear propagation. This nonlinear behavior, which includes the transfer of energy to high frequencies, is captured in the present algorithm. The generalized nonlinear Burgers equation, which includes atmospheric absorption and dissipation, is solved for the pressure signal in the frequency domain. The results are then obtained as a function of time. A test case of a sinusoidal wave is considered, and the results are compared with the existing analytical Blackstock Bridging Function (BBF) and Fubini solutions. The predicted results of the sinusoidal wave case agree fairly well with the analytical results. Data from the Boeing Low Speed Aeroacoustic Facility (LSAF) are used for the broadband noise prediction. The experimental and predicted Power Spectral Density (PSD) plots are compared for microphones at different radial locations. The predicted results are in good agreement with the experimental results at all the microphone locations, and the PSD plots show a lift at high frequencies due to the nonlinear steepening of the waves. The skewness of the experimental and predicted signal is discussed for the Boeing LSAF data. Full scale F/A-18E engine tie-down data are propagated using the nonlinear and linear predictions and the differences in the results are discussed. Ground reflection effects are then presented for both the Boeing LSAF and F/A-18E engine data.