A Fuzzy Logic-Based Energy-Adaptive Localization Scheme by Fusing WiFi and PDR
A Fuzzy Logic-Based Energy-Adaptive Localization Scheme by Fusing WiFi and PDR
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融合 WiFi 和 PDR 的基于模糊逻辑的能量自适应定位方案
DOI：
10.1155/2023/9052477
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发表时间：
2023-01
影响因子：
--
通讯作者：
Runze Yang
中科院分区：
文献类型：
--
作者：
Yankan Yang;Baoqi Huang;Zhendong Xu;Runze Yang
在智能手机上融合WiFi指纹定位和行人航位推算（PDR）颇具吸引力，因为它们在定位精度和能耗方面具有明显的互补性。尽管融合定位算法往往会提高定位精度，但所涉及的额外硬件和软件会导致额外的计算，从而不可避免地增加能耗。因此，在本研究中，我们提出了一种基于模糊逻辑的新型融合定位方案，旨在以尽可能少的能耗实现理想的定位精度。具体而言，通常调用节能的惯性测量单元（IMU）传感器以PDR的方式提供智能手机用户的位移，而采用模糊推理系统根据融合定位误差的粗略度量和智能手机的剩余电量自适应地调度耗能的WiFi扫描以实现WiFi指纹定位，从而在定位精度和能耗之间实现平衡。此外，为了减轻PDR引起的漂移误差的影响，利用一系列WiFi定位结果进一步识别用户的直线轨迹，以校准PDR的航向估计。大量实验结果表明，所提方案达到了与互补滤波器相同的精度，但能耗比互补滤波器低38.02%，证实了所提方案能够有效地平衡定位精度和能耗。
Fusing WiFi fingerprint localization and pedestrian dead reckoning (PDR) on smartphones is attractive because of their obvious complementarity in localization accuracy and energy consumption. Although fusion localization algorithms tend to improve localization accuracy, extra hardware and software involved will result in extra computations, such that energy consumption is inevitably increased. Thus, in this study, we propose a novel fusion localization scheme based on fuzzy logic, which aims to achieve ideal localization accuracy by consuming as little energy as possible. Specifically, energy-efficient inertial measurement unit (IMU) sensors are routinely called to provide the displacement of a smartphone user in the manner of PDR, whereas a fuzzy inference system is employed to adaptively schedule energy-hungry WiFi scans to fulfill WiFi fingerprint localization according to a coarse metric for fusion localization errors and the remaining energy of the smartphone, so as to achieve a trade-off between localization accuracy and energy consumption. Moreover, in order to mitigate the effect of drift errors induced by PDR, straight trajectories of the user are further identified using a series of WiFi localization results to calibrate heading estimates of PDR. Extensive experimental results demonstrate that the proposed scheme achieves the same accuracy as the complementary filter, but consumes 38.02% energy than the complementary filter, confirming that the proposed scheme can effectively balance the localization accuracy and energy consumption.
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DOI：
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发表时间：
2002
期刊：
--
影响因子：
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作者：
H. Weinberg
通讯作者：
H. Weinberg
使用无约束智能手机的新型步行检测和步数计数算法
DOI：
10.3390/s18010297
发表时间：
2018-01-19
期刊：
Sensors (Basel, Switzerland)
影响因子：
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作者：
Kang X;Huang B;Qi G
通讯作者：
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DOI：
10.1109/compsac.2019.00102
发表时间：
2019-07
期刊：
2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC)
影响因子：
--
作者：
Yankan Yang;Baoqi Huang;Runze Yang
通讯作者：
Yankan Yang;Baoqi Huang;Runze Yang
DOI：
10.1109/percomw.2011.5766963
发表时间：
2011-03
期刊：
2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)
影响因子：
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作者：
P. Tarrío;M. Cesana;M. Tagliasacchi;A. Redondi;L. Borsani;J. Casar
通讯作者：
P. Tarrío;M. Cesana;M. Tagliasacchi;A. Redondi;L. Borsani;J. Casar
DOI：
10.1109/indin.2013.6622857
发表时间：
2013-07
期刊：
2013 11th IEEE International Conference on Industrial Informatics (INDIN)
影响因子：
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作者：
J. Miranda;R. Abrishambaf;T. Gomes;Paulo Goncalves;J. Cabral;A. Tavares;J. Monteiro
通讯作者：
J. Miranda;R. Abrishambaf;T. Gomes;Paulo Goncalves;J. Cabral;A. Tavares;J. Monteiro