Real-Time NLOS/LOS Identification for Smartphone-Based Indoor Positioning Systems Using WiFi RTT and RSS

The accuracy of smartphone-based positioning systems using WiFi usually suffers from ranging errors caused by non-line-of-sight (NLOS) conditions. Previous research usually exploits several distribution features from a long time series (hundreds of samples) of WiFi received signal strength (RSS) or...

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Bibliographic Details
Published in:IEEE sensors journal 2022-03, Vol.22 (6), p.5199-5209
Main Authors: Dong, Yinhuan, Arslan, Tughrul, Yang, Yunjie
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Dispersion
Distance measurement
Feature extraction
Identification methods
Line of sight
Machine learning
positioning
Power consumption
Real time
Real-time NLOS identification
Real-time systems
Signal strength
Smart phones
smartphone
Smartphones
Testing
Time series
User experience
WiFi RSS
WiFi RTT
Wireless fidelity
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Summary:The accuracy of smartphone-based positioning systems using WiFi usually suffers from ranging errors caused by non-line-of-sight (NLOS) conditions. Previous research usually exploits several distribution features from a long time series (hundreds of samples) of WiFi received signal strength (RSS) or WiFi round-trip time (RTT) to achieve a high identification accuracy. However, the long time series or large sample size attributes to high power and time consumption in data collection for both training and testing. This will also undoubtedly be detrimental to user experience as the waiting time for getting enough samples is quite long. Therefore, this paper proposes three new real-time NLOS/LOS identification methods for smartphone-based indoor positioning systems using WiFi RSS and RTT distance measurement (RDM). Based on our extensive analysis of RSS and RDM dispersion features, three machine learning algorithms were chosen and developed to separate the samples for NLOS/LOS conditions. Experiments show that our best method achieves a discrimination accuracy of over 96% with a sample size of 10. Considering the theoretically shortest WiFi ranging interval of 100ms of the RTT-enabled smartphones, our algorithm is able to provide the shortest latency of 1s to get the testing result among all of the state-of-art methods.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2021.3119234