This paper proposes an adaptive direction of arrival (DOA) estimation method, which satisfies the dynamic signal to noise ratio (SNR) and low complexity requirement of space communications. Integrating with subspace class algorithms, this paper uses information of covariance matrix corresponding to the array received signal as feature input, adding instance selection while minimizing distribution distance of source domain and target domain, whose samples go through different SNRs and snapshots. Error of the angle estimation is employed as cost function to construct the regression model. The simulation results show that after using the training set of a specific SNR and snapshot number to get the estimation model, good angle estimation performance can be observed under a certain range of SNR and the snapshot number, which demonstrates the adaptability of the proposed algorithm.