In　the　scenario　with　reverberation,　the　experience　of　human-machine　interaction　will　become　worse.　In　order　to　solve　this　problem,　many　methods　for　the　dereverberation　have　emerged.　At　present,　how　to　update　the　parameters　of　the　Kalman　filter　in　the　existing　dereverberation　methods　based　on　multichannel　linear　prediction　(MCLP)　is　a　challenging　task,　especially,　accurate　power　spectral　density　(PSD)　estimation　of　target　speech.　In　this　paper,　minimum　variance　distortionless　response　(MVDR)　beamformer　and　MCLP　are　effectively　fused　in　the　dereverberation,　where　the　PSD　of　target　speech　used　for　Kalman　filter　is　modified　in　the　MCLP.　In　order　to　construct　a　MVDR　beamformer,　the　PSD　of　late　reverberation　and　the　PSD　of　the　noise　are　estimated　simultaneously　by　the　blocking-based　PSD　estimator.　Thus,　the　PSD　of　target　speech　used　for　Kalman　filter　can　be　obtained　by　subtracting　the　PSD　of　late　reverberation　and　the　PSD　of　the　noise　from　the　PSD　of　observation　signal.　Compared　to　the　reference　methods,　the　proposed　method　shows　an　outstanding　performance.　　©　2022　IEEE.