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Examines a new, fast, high-performance angle-of-arrival (AOA) estimator called the QR-based spectrum estimation algorithm, which the authors apply to the low-angle tracking problem in radar. They compare the performance of this algorithm to the more established modern estimators of its kind; namely, the MUSIC and modified FBLP algorithms. This comparison is based on real data collected from an experimental low-angle tracking radar simulator which was operated over water. All methods considered are adapted, using the spatial smoothing technique, so that accurate results may be obtained in the presence of correlated multipath, or from one single snapshot. It has been determined that the performance of this QR technique is virtually the same as that of MUSIC, yet does not require time-consuming eigendecompositions. Instead, the method is based on the much faster QR decomposition, which may be implemented readily using systolic arrays. Speedup factors on the order of 10 times the dimension of the covariance matrix are expected with the QR method. It has been determined that all the AOA estimators considered behave well when applied to the low-angle tracking problem.