Hybrid Wireless Localization via Complex-domain Isometric Embedding

Abstract

We revisit the super multidimensional scaling (SMDS) wireless localization algorithm first proposed a decade ago, recasting it onto the complex-domain1. Under this new formulation, the edge kernel which carries both angle and distance information simultaneously and plays a central role in the SMDS algorithm, becomes a complex-valued rank-one matrix, resulting in a new complex-domain SMDS framework which yields several advantages over the original, including the elimination of redundancy and the enhancement of conditions to handle information erasure.