The radio telescope possesses high sensitivity and strong signal collection capabilities. While receiving celestial radiation signals, it also captures Radio Frequency Interferences (RFIs) introduced by human activities. RFI, as signals originating from sources other than the astronomical targets, significantly impacts the quality of astronomical data. This paper presents an RFI fast mitigation algorithm based on block Least Mean Square (LMS) algorithm. It enhances the traditional adaptive LMS filter by grouping L adjacent time-sampled points into one block and applying the same filter coefficients for filtering within each block. This transformation reduces multiplication calculations and enhances algorithm efficiency by leveraging the time-domain convolution theorem. The algorithm is tested using baseband data from the Parkes 64 m radio telescope's pulsar observations and simulated data. The results confirm the algorithm's effectiveness, as the pulsar profile after RFI mitigation closely matches the original pulsar profile.

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