Abstract
Localization of mobile station (MS) is a very popular research topic at present. In this study, a novel complex framework of multidimensional scaling (MDS) algorithm for positioning a stationary target is introduced by utilizing time-of-arrival measurements collected by passive base stations (BSs). The complex MDS framework is based on the transformation of complex coordinates extending the dimension of noise subspace for positioning and strengthening the constraints between BSs and MS. Computer simulations are included to verify the development and to contrast the estimator performance with their corresponding real versions as well as the Cramer---Rao lower bound. It is shown that each complex method has lower mean square position errors and more robust than its real version.
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