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The authors propose two algorithms for anchorless cooperative network localization in mobile Wireless Sensor Networks (WSNs). In order to continuously localize the mobile network, given the pairwise distance measurements between different wireless sensor nodes, they propose to use subspace tracking to track the variations in signal eigenvectors and corresponding eigen-values of the double-centered distance matrix. They compare the computational complexity of the proposed algorithms with a recently developed anchorless algorithm exploiting the Extended Kalman filter (EKF) as well as an anchored algorithm exploiting ordinary Least Squares (LS).
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