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Multiantenna GNSS systems allow for direction of arrival (DOA) measurements, which enable the system to estimate attitude and authenticate incoming signals. Typical multiantenna systems use meter length baselines and differenced carrier phase ranges to estimate direction of arrival. However, a controlled reception pattern antenna (CRPA) has sub carrier wavelength antenna separations, making it less than ideal for traditional DOA techniques. Instead, DOA methods from other disciplines can be applied to the GNSS signal, provided the signal is visible above the thermal noise floor. The GNSS signal is elevated above the noise floor by correlating the signal at each antenna element to recreate an GNSS baseband signal from correlator outputs that retains the original signal phase information. This work investigates three methods of direction of arrival estimation using a CRPA on post correlated GNSS signals: Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT), and carrier phase differences. The data used to evaluate these algorithms was simulated by Orolia’s Skydel software and post processed in MATLAB. The algorithms were evaluated on runtime, measurement accuracy, and attitude accuracy for a full visible constellation in a series of tests with degrading carrier to noise density ratios (CN0). The MUSIC algorithm provided the best results at the cost of the longest runtime. However, adaptions proposed for this use case enabled significant computational savings. Next, carrier phase differences provided less accurate results but was computationally the cheapest algorithm. Finally, ESPIRIT had the least accurate results, while having a fast runtime.