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Abstract

Positioning information greatly enhances the convenience of people’s lives and the efficiency of societal operations. However, due to the impact of complex indoor environments, GNSS signals suffer from multipath effects, blockages, and attenuation, making it difficult to provide reliable positioning services indoors. Smartphone indoor positioning and navigation is a crucial technology for enabling indoor location services. Nevertheless, relying solely on a single positioning technique can hardly achieve accurate indoor localization. We reviewed several main methods for indoor positioning using smartphone sensors, including Wi-Fi, Bluetooth, cameras, microphones, inertial sensors, and others. Among these, wireless medium-based positioning methods are prone to interference from signals and obstacles in the indoor environment, while inertial sensors are limited by error accumulation. The fusion of multi-source sensors in complex indoor scenarios benefits from the complementary advantages of various sensors and has become a research hotspot in the field of pervasive indoor localization applications for smartphones. In this paper, we extensively review the current mainstream sensors and indoor positioning methods for smartphone multi-source sensor fusion. We summarize the recent research progress in this domain along with the characteristics of the relevant techniques and applicable scenarios. Finally, we collate and organize the key issues and technological outlooks of this field.

Details

1009240
Business indexing term
Title
Indoor Localization Methods for Smartphones with Multi-Source Sensors Fusion: Tasks, Challenges, Strategies, and Perspectives
Author
Liu, Jianhua 1   VIAFID ORCID Logo  ; Yang, Zhijie 1 ; Zlatanova, Sisi 2   VIAFID ORCID Logo  ; Li, Songnian 3   VIAFID ORCID Logo  ; Yu, Bing 1 

 Mobile Geospatial Big Data Cloud Service Innovation Team, School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 102616, China; [email protected] (Z.Y.); [email protected] (B.Y.) 
 School of Built Environment, The University of New South Wales, Sydney, NSW 2052, Australia; [email protected] 
 Department of Civil Engineering, Toronto Metropolitan University, 350 Victoria Street, Toronto, ON M5B 2K3, Canada; [email protected] 
Publication title
Sensors; Basel
Volume
25
Issue
6
First page
1806
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
e-ISSN
14248220
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-03-14
Milestone dates
2024-12-25 (Received); 2025-03-11 (Accepted)
Publication history
 
 
   First posting date
14 Mar 2025
ProQuest document ID
3181751515
Document URL
https://www.proquest.com/scholarly-journals/indoor-localization-methods-smartphones-with/docview/3181751515/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-03-27
Database
ProQuest One Academic