ArticleSensors (Basel, Switzerland)2018
An INS/WiFi Indoor Localization System Based on the Weighted Least Squares.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A Method for Autonomous Multi-Motion Modes Recognition and Navigation Optimization for Indoor Pedestrian.Sensors (Basel, Switzerland) · 2022Article
- Indoor Localization Method of Personnel Movement Based on Non-Contact Electrostatic Potential Measurements.Sensors (Basel, Switzerland) · 2022Article
- An Indoor Navigation Algorithm Using Multi-Dimensional Euclidean Distance and an Adaptive Particle Filter.Sensors (Basel, Switzerland) · 2021Article
- Dynamic Indoor Localization Using Maximum Likelihood Particle Filtering.Sensors (Basel, Switzerland) · 2021Article
- Improved Position Accuracy of Foot-Mounted Inertial Sensor by Discrete Corrections from Vision-Based Fiducial Marker Tracking.Sensors (Basel, Switzerland) · 2020Article
- Construction of Hybrid Dual Radio Frequency RSSI (HDRF-RSSI) Fingerprint Database and Indoor Location Method.Sensors (Basel, Switzerland) · 2020Article
- An Adaptive Bluetooth/Wi-Fi Fingerprint Positioning Method based on Gaussian Process Regression and Relative Distance.Sensors (Basel, Switzerland) · 2019Article
- CC-DTW: An Accurate Indoor Fingerprinting Localization Using Calibrated Channel State Information and Modified Dynamic Time Warping.Sensors (Basel, Switzerland) · 2019Article
- Smartphone Heading Correction Based on Gravity Assisted and Middle Time Simulated-Zero Velocity Update Method.Sensors (Basel, Switzerland) · 2018Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
For smartphone indoor localization, an INS/WiFi hybrid localization system is proposed in this paper. Acceleration and angular velocity are used to estimate step lengths and headings. The problem with INS is that positioning errors grow with time. Using radio signal strength as a fingerprint is a widely used technology. The main problem with fingerprint matching is mismatching due to noise. Taking into account the different shortcomings and advantages, inertial sensors and WiFi from smartphones are integrated into indoor positioning. For a hybrid localization system, pre-processing techniques are used to enhance the WiFi signal quality. An inertial navigation system limits the range of WiFi matching. A Multi-dimensional Dynamic Time Warping (MDTW) is proposed to calculate the distance between the measured signals and the fingerprint in the database. A MDTW-based weighted least squares (WLS) is proposed for fusing multiple fingerprint localization results to improve positioning accuracy and robustness. Using four modes (calling, dangling, handheld and pocket), we carried out walking experiments in a corridor, a study room and a library stack room. Experimental results show that average localization accuracy for the hybrid system is about 2.03 m.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.