Recent advances in mobile devices and ubiquity of wireless infrastructures create the opportunity to utilize heterogeneous wireless networks (HWNs) for localization. To efficiently exploit the spatial correlation embedded in the measurements from HWNs, we proposed two algorithms via a cooperative approach, called Direct Multi-Radio Fusion and Cooperative Eigen- Radio Positioning. The former discovers the spatial correlation after the information of measurements is reorganized to minimize the redundancy. The latter takes a further step to incorporate the spatial discrimination to estimate the location. We have implemented our algorithms for different wireless technologies involving the cellular GSM, DVB, FM and WLAN in realistic outdoor/indoor environments. The results show that the proposed algorithm reduces 44.19-48.88% of the mean error, as compared to the conventional approaches.
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Fang et al. (2010) studied this question.
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