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| In the node localization problem of wireless sensor networks(WSNs), distance measurements are often corrupted by large errorswhich will lead to inaccurate position estimates withoutcorrection. To address this issue, we propose a scheme of jointnode localization and error correction from distance measurements ofWSNs. The enabling fact is that only a small number of distancemeasurements are subject to large errors in general. Such extit{sparsity} motivates us to propose an $ell_1$ regularizednonlinear least squares model, where the $ell_1$ regularizationterm promotes the sparsity of large errors and the nonlinear leastsquares term reflects the fidelity of distance measurements. Thisnonconvex model is further relaxed to a second-order coneprogramming (SOCP) problem, which is convex and tractable.Extensive simulations demonstrate the effectiveness of theproposed approach. |
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| Keywords:wireless sensor networks (WSNs), node localization, error correction, second-order cone programming (SOCP) |
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