1673-159X

CN 51-1686/N

张益,李飞. 基于信号强度差值的改进质心定位算法[J]. 西华大学学报(自然科学版),2024,43(3):1 − 7. doi: 10.12198/j.issn.1673-159X.5086
引用本文: 张益,李飞. 基于信号强度差值的改进质心定位算法[J]. 西华大学学报(自然科学版),2024,43(3):1 − 7. doi: 10.12198/j.issn.1673-159X.5086
ZHANG Yi, LI Fei. Improved Centroid Localization Algorithm Based on Signal Strength Difference[J]. Journal of Xihua University(Natural Science Edition), 2024, 43(3): 1 − 7.. DOI: 10.12198/j.issn.1673-159X.5086
Citation: ZHANG Yi, LI Fei. Improved Centroid Localization Algorithm Based on Signal Strength Difference[J]. Journal of Xihua University(Natural Science Edition), 2024, 43(3): 1 − 7.. DOI: 10.12198/j.issn.1673-159X.5086

基于信号强度差值的改进质心定位算法

Improved Centroid Localization Algorithm Based on Signal Strength Difference

  • 摘要: 质心算法用于室内定位时具有实现简单及综合开销小的特点,但定位精度及稳定性较差。为解决该问题,文章利用信号强度(RSSI)差值对质心算法进行改进。将参与定位的参考节点部署为形如等腰直角三角形的定位区域,并采用缩小定位区域的思想将定位区域按照三角形顶点垂直平分线均匀划分为4个定位子区域。在定位过程中,获取信号强度值最大3个参考节点并判断是否构成等腰直角三角形,若满足条件则通过计算参考节点三角形各顶点间信号强度差值以判断目标节点所处子区域,最后计算所聚焦子区域的质心坐标作为最终定位结果。仿真结果表明,改进算法相比传统的质心定位算法及三边质心算法具有更高的定位精度和更好的稳定性,且因改进算法避免了使用路径损耗函数,减少了前期参考节点部署工作量。该改进算法是一种较为简单、实用,并且精度和稳定性较高的室内定位算法,适用于各种室内无线定位系统。

     

    Abstract: Indoor positioning is an important research field in current intelligent construction. The centroid algorithm is characterized by its simplicity and low computational cost for indoor positioning. However, it suffers from poor positioning accuracy and stability. To address this issue, an improvement is proposed by utilizing the difference in signal strength (RSSI) in the centroid algorithm. The improved centroid positioning algorithm based on RSSI difference requires deploying the reference nodes involved in positioning as a localization area in the form of an isosceles right triangle. The idea of narrowing down the localization area is employed by dividing the area evenly into four sub-areas along the perpendicular bisectors of the triangle's vertices. During the positioning process, the three reference nodes with the strongest signal strengths are selected, and it is checked if they form an isosceles right triangle. If the condition is met, the sub-area where the target node is located is determined by calculating the signal strength differences between the vertices of the reference node triangle. Finally, the centroid coordinates of the focused sub-area are computed as the final positioning result. Simulation results demonstrate that the improved algorithm outperforms the traditional centroid positioning algorithm and the three-side centroid algorithm in terms of higher positioning accuracy and better stability. Moreover, the improved algorithm avoids the need for using path loss functions, reducing the deployment workload of reference nodes in the early stages. Therefore, the improved algorithm is a relatively simple, practical, and highly accurate and stable indoor positioning algorithm suitable for various indoor wireless positioning systems.

     

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