In order to cut down the hardware cost and reduce the inter element mutual coupling, a directionofarrival (DOA) estimator based on differenceset table traversal searching for co-prime sparse arrays is proposed. This estimator concurrently possesses both low computational complexity and high precision. On the one hand, the low computational complexity lies in: the sensor coordinates in a sparse coprime array can be easily utilized to construct a differenceset table; guided by this table, the observed array’s covariance matrix can be readily converted to the Nyquist virtual array’s covariance matrix, from which multiple objects’ final DOA estimation can be directly calculated by means of multiple signal classification decomposition. On the other hand, the high accuracy lies in: the proposed measure of differenceset table traversal searching is able to enhance the dimension of the signal subspace, which actually improves the resolution of the spatial spectrum. In view of the tendency that the array signal processing applications in higher frequency band and shorter wavelength are increasingly widened, the proposed DOA estimator possesses a vast potential for future development.