室内定位算法基于信息获取比率和亲和传播聚类的信息获取比率
Rencheng Jin1, Di Zhang1, Xiao Tian1
1Key Laboratory for Micro/Nano Technology and System of Liaoning Province, Dalian University of Technology, Dalian 116024, China.
Sensors (Basel, Switzerland)
|January 28, 2026
概括
本研究介绍了一种方法,可以在室内定位系统中删除多余的接入点 (AP),显著减少数据库大小,同时保持准确性. 与现有方法相比,新方法还可以提高定位准确度,减少错误.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 信号处理 信号处理
背景情况:
- 室内定位系统通常使用Wi-Fi接入点 (AP) 来进行指纹识别.
- 冗余的AP增加了计算负载,并提供了越来越少的准确性改进.
- 现有的方法缺乏在指纹数据库中选择AP的有效策略.
研究的目的:
- 提出一种新的方法来消除室内定位系统中多余的AP.
- 为了减少计算负载和数据库大小,而不会影响定位准确度.
- 为了提高室内定位估计的准确性和减少误差.
主要方法:
- 计算AP位置歧视能力,并将其与AP消除的覆盖率相结合.
- 使用亲和力传播集群来进行粗略的定位.
- 采用贝叶斯的方法来精确定位.
主要成果:
- 移除AP的策略将指纹数据库大小减少了高达72.78%,同时保持了在5%的波动范围内定位准确度.
- 与GMM,K-Means和点向算法相比,拟议的定位方法将平均定位误差降低了11%至39%.
- 在现实世界和基准数据集上的实验验证证证了拟议方法的有效性.
结论:
- 开发的AP消除策略有效地优化了用于室内定位的指纹数据库.
- 结合粗微定位方法显著提高准确性,减少错误.
- 这项研究为高效准确的室内定位提供了实际解决方案.
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