The data of Doppler weather radar are often contaminated by ground clutter. It has a significant effect on the accuracy of the base data estimates (reflectivity, velocity and spectrum width), then it will also affect all ensuing products. Therefore, filtering techniques that attempt to suppress these ground clutter signals are essential for high data quality in all Doppler weather radar systems. Firstly, this dissertation outlines the research background and significance of adaptive Gaussian frequency filter. Secondly, analyzes the characteristics of the ground clutter and weather signals in the Doppler weather radars. Thirdly, describes the theory of the fifthorder elliptic infinite impulse response (IIR) ground clutter filter and the algorithm of adaptive Gaussian frequency filter. In the end, using the data of actual radar echo signals, analyzes the ground clutter suppression performance of the fifthorder elliptic infinite impulse response (IIR) ground clutter filter and adaptive Gaussian frequency filter. Then, analyzes and compares the ground clutter suppression performance of these two methods, gets following results: the ground clutter suppression performance of the adaptive Gaussian frequency filter without clutter filter bypass charts is better than that of the fifthorder elliptic IIR filter with clutter filter bypass charts, and adaptive Gaussian frequency filter satisfies the request of realtime processing.