This paper discusses the selection of window function for signal processing in microwave imaging brain tumor detection. Most of the window functions are non-negative bell-shaped curves. This paper proposed a superposition windowing function for better time series data analyses and enhancement. The performance of the selected five window functions (Hamming, Blackman-Harris, Parzen, Chebyshev and Bartlett-Hanning) and the proposed superposition window were compared and evaluated. The results show the superposition window function is potentially reduce the unwanted noise and preserve important information of the signals.