最小定位误差的信标节点布置
Beacon Node Placement for Minimal Localization Error
摘要：
信标节点放置、节点到节点测量和目标节点定位是定位过程的三个关键步骤。然而，与其他两个步骤相比，信标节点的放置在研究文献中还缺乏全面、系统的研究。为了填补这一空白，我们解决信标节点放置（BNP）的问题，部署信标节点的最小定位误差在本文中。BNP是困难的，因为定位误差是由复杂的因素组合确定的，即，定位误差在不同的环境下、在应用不同的算法的情况下、或者在使用不同类型的信标节点的情况下差别很大。针对BNP算法的困难性，提出了一种近似函数来减少定位误差计算的时间开销，并证明了其时间复杂度和误差界。通过近似，可以在可接受的时间成本内找到信标节点的次优分布。在实验中，我们测试了我们的方法，并将其与其他节点放置方法在各种设置和环境下进行比较。实验结果表明了该方法的可行性和有效性。
英文摘要：
Beacon node placement, node-to-node measurement, and target node positioning are the three key steps for a localization process. However, compared with the other two steps, beacon node placement still lacks a comprehensive, systematic study in research literatures. To fill this gap, we address the Beacon Node Placment (BNP) problem that deploys beacon nodes for minimal localization error in this paper. BNP is difficult in that the localization error is determined by a complicated combination of factors, i.e., the localization error differing greatly under a different environment, with a different algorithm applied, or with a different type of beacon node used. In view of the hardness of BNP, we propose an approximate function to reduce time cost in localization error calculation, and also prove its time complexity and error bound. By approximation, a sub-optimal distribution of beacon nodes could be found within acceptable time cost for placement. In the experiment, we test our method and compare it with other node placement methods under various settings and environments. The experimental results show feasibility and effectiveness of our method in practice.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
