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Linear array-based three-dimensional (3-D) localization is a recently proposed technology. It uses a set of newly defined one-dimensional (1-D) angles, called space angle (SA), to locate the source. Integrating SA with time difference of arrival (TDOA) promises higher accuracy, and more attractive, provides the formulation leading to closedform solutions. Currently, studies of hybrid SA-TDOA localization leverage iteration to refine the performance to the Cramer-Rao lower' bound (CRLB), which suffers from the possible convergence issues. This paper advances this topic by proposing a two-stage weighted least squares (TSWLS) closed-form estimator, which avoids the risk of divergence and can attain the CRLB if the noise is mild. Analytical and numerical results show the performance ascendancy of the proposed method.
Xing et al. (Mon,) studied this question.