Abstract: The conventional MVDR adaptive beamformer is a high-resolution narrowband beamformer which estimates the optimal beamforming weights using narrowband CSDM of real acoustic field.In practical applications,MVDR algorithm needs long observation time to estimate the covariance matrix.This inherent property makes it difficult to localize fast-moving targets.For wideband signals,MVDR algorithm needs invert every CSDM which increases the computational load.For correlated sources,the performance of MVDR will degrade dramatically because the signals will cancel each other.A fast-convergent MVDR algorithm based on subband subarray processing is proposed.The full frequency band is divided into sets of subbands and the line array is divided into sets of subarrays.For every subband the STCM of reduced dimension is calculated.Then the adaptive beamforming weight of fast-convergent MVDR algorithm and spatial spectrum estimation are obtained.At the same time,spatial spectrum estimation can be made for correlated sources using the two-sided spatial smoothing method.Resultsof simulation and trial data show that the proposed method has high-resolution and near-instantaneous convergence property,two-sided spatial smoothing has satisfactory validity of decorrelation.