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We present an algorithm for distributed sensor localization with noisy distance measurements (DILAND) that extends and makes the DLRE more robust. DLRE is a distributed sensor localization algorithm in Rm (m ?? 1) introduced in our previous work (IEEE Trans. Signal Process., vol. 57, no. 5, pp. 2000-2016, May 2009). DILAND operates when: 1) the communication among the sensors is noisy; 2) the communication...
In this paper, we review our work on distributed sensor localization using barycentric coordinates. We present an algorithm for localization in m-dimensional Euclidean spaces. The algorithm is distributed and requires at least m + 1 anchors. Anchors are the nodes that know their exact locations. We require that the nonanchor nodes (all the network nodes that do not know their locations) lie in the...
This paper presents a distributed sensor localization algorithm with inter-sensor distance information in m-dimensional Euclidean space using only m + 1 anchors (sensors that know their exact locations). Under the assumption that the M sensors (with unknown locations) lie in the convex hull of the m + 1 anchors and the underlying network is connected, we derive a linear algorithm that employs barycentric...
The authors presented an algorithm to localize sensors in m-dimensional Euclidean space Ropfn with unknown locations assuming the following: (1) there are (m + 1) sensors that know their absolute coordinates-the anchors; (2) each sensor communicates with m + 1 of its neighbors; and (3) the sensors lie in the convex hull of the anchors. The localization algorithm is a generalization of consensus-it...
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