In order to solve the problem of low computational efficiency of adaptive beamforming algorithms in ultrasonic imaging, an adaptive beamforming algorithm for ultrasonic array with the combination of spatial sampling and coherence factor was proposed. The maximum decimation factor with different numbers of array elements was deduced according to the beam pattern. The sparse echo data was obtained by spatially sampling the whole array element data using the maximum decimation factor. Therefore, the amount of data used for beamforming was greatly reduced. Taking the spatial sampling data as the input of a beamformer and constructing the covariance matrix as Toeplitz matrix, the adaptive weights of the sampling data were obtained according to the principle of minimum variance. Then, the adaptive weights were modified by introducing the coherence factor to highlight the effective information of the sampling data. Under the case of unequal data and spatial sampling data, the proposed algorithm, minimum variance algorithm and minimum variance algorithm combined with coherence factor were used to simulate the imaging of cracks and cross-drilled holes respectively. The results show that: for unequal data, the imaging quality of the proposed algorithm is between the other two algorithms; in terms of imaging time, compared with the other two algorithms, the average imaging time of the proposed algorithm is reduced by more than 85%. For the same spatial sampling data, the imaging quality of the proposed method is better than the other algorithms; in terms of imaging time, compared with the other two algorithms, the average imaging time of the proposed algorithm is reduced by more than 65%.