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On geometric upper bounds for positioning algorithms in wireless sensor networks

机译:无线传感器网络中定位算法的几何上限

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This paper studies the possibility of upper bounding the position error for range-based positioning algorithms in wireless sensor networks. In this study, we argue that in certain situations when the measured distances between sensor nodes have positive errors, e.g., in non-line-of-sight (NLOS) conditions, the target node is confined to a closed bounded convex set (a feasible set) which can be derived from the measurements. Then, we formulate two classes of geometric upper bounds with respect to the feasible set If an estimate is available, either feasible or infeasible, the position error can be upper bounded as the maximum distance between the estimate and any point in the feasible set (the first bound). Alternatively, if an estimate given by a positioning algorithm is always feasible, the maximum length of the feasible set is an upper bound on position error (the second bound). These bounds are formulated as nonconvex optimization problems. To progress, we relax the nonconvex problems and obtain convex problems, which can be efficiently solved. Simulation results show that the proposed bounds are reasonably tight in many situations, especially for NLOS conditions.
机译:本文研究了无线传感器网络中基于距离的定位算法的上限误差的可能性。在这项研究中,我们认为在某些情况下,当传感器节点之间的测量距离具有正误差时,例如在非视距(NLOS)条件下,目标节点将被限制在一个封闭的有界凸集内(可行设置),可以从测量中得出。然后,我们针对可行集制定两类几何上限。如果估计可用(可行或不可行),则位置误差可以作为估计与可行集中任意点之间的最大距离的上限第一界)。替代地,如果由定位算法给出的估计总是可行的,则可行组的最大长度是位置误差的上限(第二界限)。这些界限被公式化为非凸优化问题。为了进步,我们放松了非凸问题并获得了凸问题,可以有效地解决这些问题。仿真结果表明,在许多情况下,特别是在非视距条件下,建议的边界都相当严格。

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