• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2022, Vol. 44 ›› Issue (04): 645-653.

• 计算机网络与信息安全 • 上一篇    下一篇

融合正余弦优化与跳距优化的DV-Hop定位算法

张晶1,2,3,4,贺媛媛1,3,4   

  1. (1.昆明理工大学信息工程与自动化学院,云南 昆明 650500;2.云南枭润科技服务有限公司,云南 昆明 650500;
    3.昆明理工大学云南省人工智能重点实验室,云南 昆明 650500;
    4.昆明理工大学云南省计算机技术应用重点实验室,云南 昆明 650500)

  • 收稿日期:2020-02-14 修回日期:2021-03-22 接受日期:2022-04-25 出版日期:2022-04-25 发布日期:2022-04-20
  • 基金资助:
     云南省基础研究计划重点项目(202101AS070016);2020年云南省研究生优质课程“算法分析与设计”建设项目(109920210048);云南省“万人计划”产业技术领军人才项目(云发改人事[2019]1096号);云南省技术创新人才项目(2019HB113)

A DV-Hop positioning algorithm combining sine and cosine optimization and hop distance optimization

ZHANG Jing 1,2,3,4,HE Yuan-yuan1,3,4   

  1. (1.Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500;
    2.Yunnan Xiaorun Technology Service Co.,Ltd.,Kunming 650500;
    3.Yunnan Key Laboratory of Artificial Intelligence,Kunming University of Science and Technology,Kunming 650500;
    4.Key Laboratory of Computer Technology Application of Yunnan Province,
    Kunming University of Science and Technology,Kunming 650500,China)
  • Received:2020-02-14 Revised:2021-03-22 Accepted:2022-04-25 Online:2022-04-25 Published:2022-04-20

摘要: 针对DV-Hop定位算法中跳距计算不精确以及最小二乘法求解不能达到最优无偏状态导致定位不准确的问题,提出一种融合正余弦优化与跳距优化的DV-Hop定位算法,并给出了最优化锚节点的概念。该算法首先选取每个未知节点周围所有锚节点中平均跳距最小的锚节点作为最优化锚节点;然后选取其余任一锚节点与未知节点构成三角形,将最优化锚节点到未知节点的边作为三角形中的最优化边;其次利用余弦定理计算其余锚节点到未知节点的距离,达到优化跳距的目的;最后利用正余弦优化算法改进最小二乘法,利用正余弦函数的波动性寻找未知节点的最优位置。实验结果表明,该算法相比于传统DV-Hop定位算法和DV-Hop改进算法,定位误差明显降低。

关键词: 跳距优化, 正余弦优化算法, 非测距, 最优化锚节点

Abstract: In order to solve the problems of imprecise calculation of the hop distance and inaccurate positioning due to the inability of the least squares solution to reach the optimal unbiased state in the DV-Hop positioning algorithm, a DV-Hop positioning algorithm combining sine and cosine optimization and hop distances optimization is proposed, which defines the concept of the optimised anchor node. Firstly, the anchor node with the smallest average hop distance among all anchor nodes around each unknown node is selected as the optimized anchor node in the algorithm, then any other anchor node is selected to form a triangle with other unknown nodes, and the edge from the optimal anchor node to the unknown node is considered to be the optimal edge in the triangle. Secondly, the distances from the other anchor nodes to the unknown nodes are calculated to optimize the hop distances by the law of cosine. Finally, the sine-cosine optimization algorithm is used to improve the least square method, and the volatility of the sine-cosine function is used to find the optimal position of the unknown node. The experimental results indicate that, compared with the conventional DV-Hop and DV-Hop improvement algorithms, the proposal reduces the positioning error significantly.


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