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The method of adaptive network fuzzy inference system (ANFIS) applied to the interference cancellation system of radar seeker was described in this paper. When the antiaircraft missile, which adopts the pulse Doppler radar seeker, attacks the low altitude target in the down-looking mode, the seeker of missile will receive strong ground clutter. As we all know the ground clutter will seriously affect the seeker's properties of target detecting and real-time tracking. To dealing with the seeker signal, the model of clutter should be constructed firstly. But it is difficult to handle because of the uncertainties and non-completeness characteristic of the clutter model. In order to solve the problem and overcome these, the nonlinear model, which used for clutter signal processing by the ANFIS is accepted in the interference cancellation system. In some researches, it was proved that the artificial network based on ANFIS not only has the ability of nonlinear mapping but also has the function of self-learning. Especially, ANFIS has small calculating costs. In my study, to possess a desired robust model, the adaptive side lobe clutter cancellation system depended on ANFIS was introduced. Through the side lobe clutter cancellation, the signal noise ratio (SNR) of echo signal got obviously improvement. The simulation results of experiments showed that the method of ANFIS can sharply improve the detecting performance of pulse Doppler radar seeker's looking for lower altitude target.