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In this study, the problem of low-complexity direction-of-arrival (DOA) estimation is addressed, and a novel real-valued propagator method (PM) is presented with a uniform linear array. The covariance matrix is divided into two subarrays and an equivalent noise subspace is obtained by exploiting the standard PM algorithm without eigenvalue decomposition. By a coordinate mapping technique, the complex PM cost function has been converted into a real-valued polynomial whose order only rely on the number of arrays. Using such a mathematical fact, source DOAs can be estimated by polynomial rooting instead of peak searching. The proposed method is able to reduce significant complexity with comparable root-mean-square error performance to the standard PM, which is finally verified by numerical simulations.