基于混合测量的无线传感器网络目标定位分布式算法在连接故障情况下的性能分析

David Vicente, Slavisa Tomic, M. Beko, R. Dinis
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引用次数: 0

摘要

本文分析了最近提出的两种用于协同三维无线传感器网络(WSNs)的分布式定位算法在更现实场景下的性能。经过测试的算法分别依赖于从接收信号强度(RSS)和到达角(AoA)信息中获得的距离和角度测量。然后利用测量结果推导出一个基于二阶锥规划(SOCP)松弛技术的凸估计量,以及一个可以表述为广义信赖域子问题(GTRS)的非凸估计量。这两个估计器在静态网络场景下都表现出了出色的性能,除了在很少的迭代中收敛之外,还提供了准确的位置估计。在这里,我们考虑了广播阶段相邻节点之间通信失败的不同概率来测试它们的性能。我们的模拟表明,它们的性能在通信故障的高概率下仍然保持不变,并且在合理数量的迭代中仍然实现收敛。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance analysis of a distributed algorithm for target localization in wireless sensor networks using hybrid measurements in a connection failure scenario
This paper presents a performance analysis of two recently proposed distributed localization algorithms for cooperative 3-D wireless sensor networks (WSNs) in a more realistic scenario. The tested algorithms rely on distance and angle measurements obtained from received signal strength (RSS) and angle-of arrival (AoA) information, respectively. The measurements are then used to derive a convex estimator, based on second order cone programming (SOCP) relaxation techniques, and a non-convex one that can be formulated as a generalized trust region sub-problem (GTRS). Both estimators have shown excellent performance assuming a static network scenario, giving accurate location estimates in addition to converging in few iterations. Here, we test their performance considering different probabilities of communication failure between neighbour nodes at the broadcast phase. Our simulations show that their performance holds for high probability of communication failure and that convergence is still achieved in a reasonable number of iterations.
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