The problem of estimating the steering vectors of an uncalibrated array is considered. We identify a cost function whose minimizer is a statistically consistent estimate of the unknown parameters. Next, we present an iterative algorithm for finding a local minimum of that cost function. The proposed algorithm is guaranteed to converge. The performance of the algorithm is compared with the Cramer-Rao bound (CRB).