Estimation accuracy and computational complexity are two major areas of consideration for localization system design. For time-of-arrival based systems, the 1st-order method of moments (MOM) least-squares (LS) estimator is simple to implement, but its performance is much worse than that of some computationally more complex estimators such as the MOM weighted LS (WLS) and nonlinear weighted LS (NLLS-WLS) estimators. In this paper, we develop an improved 1st-order MOM estimator to efficiently utilize the variances of the range measurements and the target position that, as the NLLS estimator, has a performance also approaching the Crammer-Rao lower bound but is much simpler than MOM-WLS and NLLS-WLS estimators.
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Qiao et al. (2013) studied this question.
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