The analysis of a time series is a key challenge in making use of the radar data. The challenge at hand is figuring out how to get the most value out of the data by gleaning the insights already there. It has been common practise to do time-domain or frequency-domain analyses of radar data. The Fourier Transform is one of the most fundamental tools that may be utilised in the processing and analysis of radar data. On the other hand, one of the things that stands out the most to us while analysing radar data is the fluctuation in frequency content over the course of time. Radar signals are not stationary in nature since the frequency content of these signals changes over the course of time. In recent years, there has been progress made in the use of time-frequency approaches to focus skewed radar pictures. Because of the application of these techniques, both the capability to detect and visually identify targets in SAR and ISAR has been significantly improved. The time-frequency S-method is the foundation of our method for real-time motion compensation, picture production, and image augmentation of moving targets in ISAR and SAR. This method is founded on the fact that we invented the method. This technique outperforms the Fourier transform by increasing the signal-to-noise ratio (SNR) in both low-noise and high-noise environments, which makes it ideally suited for photographing subjects that are moving quickly.