基于核密度的无线电地图优化,利用人体轨迹进行室内定位

3区 计算机科学 Q1 Computer Science
Yun Fen Yong, Chee Keong Tan, Ian K. T. Tan, Su Wei Tan
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引用次数: 0

摘要

由于室内环境的复杂性,准确的室内定位仍然是一项重大挑战。本文提出了一种基于核密度估计(KDE)和人类轨迹(HT)构建无线电地图(RM)的新方法,以提高室内定位的准确性。所提出的方法在构建 RM 时利用了历史 HT 数据,以捕捉室内环境的空间变化和复杂性,这对精确定位至关重要。通过使用 KDE,可生成内核密度图,识别出高密度区域,在这些区域战略性地放置额外的插值指纹,以提高定位精度。与均匀放置插值点(IP)的传统方法相比,所提出的方法能更好地模拟自然行走模式和轨迹,从而提高用户位置识别的独特性和准确性。通过对各种 HT 模式的大量实验,所提出的 KDE-RM 优化方法始终优于使用克里金法和反距离加权插值均匀分布 IP 的传统方法,最高可达 36.4%。这证明了所提方法的有效性和潜力,是增强室内定位的重要工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Kernel density-based radio map optimization using human trajectory for indoor localization

Kernel density-based radio map optimization using human trajectory for indoor localization

Accurate indoor localization remains a significant challenge due to the complex nature of indoor environments. This paper proposes a novel method for constructing a radio map (RM) based on Kernel density estimation (KDE) and human trajectories (HT) to enhance indoor localization accuracy. The proposed method utilizes historical HT data in RM construction to capture the spatial variability and complexity of indoor environments, which is crucial for accurate localization. By employing KDE, kernel density maps are generated, identifying high-density regions where additional interpolated fingerprints are strategically placed to improve localization accuracy. In contrast to the conventional method of uniformly placing interpolated points (IPs), the proposed approach better models natural walking patterns and trajectories, thereby enhancing the uniqueness and accuracy of user position identification. Through extensive experiments with various HT patterns, the proposed KDE-RM optimization method consistently outperforms the conventional approach of evenly distributed IPs using Kriging and inverse distance weighting interpolation by up to 36.4%. This demonstrates the effectiveness and potential of the proposed method as a valuable tool for enhancing indoor localization.

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来源期刊
Journal of Ambient Intelligence and Humanized Computing
Journal of Ambient Intelligence and Humanized Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
9.60
自引率
0.00%
发文量
854
期刊介绍: The purpose of JAIHC is to provide a high profile, leading edge forum for academics, industrial professionals, educators and policy makers involved in the field to contribute, to disseminate the most innovative researches and developments of all aspects of ambient intelligence and humanized computing, such as intelligent/smart objects, environments/spaces, and systems. The journal discusses various technical, safety, personal, social, physical, political, artistic and economic issues. The research topics covered by the journal are (but not limited to): Pervasive/Ubiquitous Computing and Applications Cognitive wireless sensor network Embedded Systems and Software Mobile Computing and Wireless Communications Next Generation Multimedia Systems Security, Privacy and Trust Service and Semantic Computing Advanced Networking Architectures Dependable, Reliable and Autonomic Computing Embedded Smart Agents Context awareness, social sensing and inference Multi modal interaction design Ergonomics and product prototyping Intelligent and self-organizing transportation networks & services Healthcare Systems Virtual Humans & Virtual Worlds Wearables sensors and actuators
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