Review on UWB-based and multi-sensor fusion positioning algorithms in indoor environment

Zhang, Hao; Zhang, Zhishu; Zhao, Ran; Lu, Jianfeng; Wang, Yan; Jia, Ping

doi:10.1109/iaeac50856.2021.9390630

Cited by 10 publications

(5 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Methods. Data fusion was first applied in the military field, which is a multilevel and multifaceted data processing process [11,12]. It is used to process multisource information and naturally identify, join, correspond, gauge, and blend data, basically to accomplish more precise position deduction and personality assessment and afterward make an opportune and complete assessment of war zone conditions, danger level, and significance level.…”

Section: Analysis Of Multisource Data Fusionmentioning

confidence: 99%

[Retracted] Design of Moral Education Management System for Higher Vocational Students Based on Multisource Sensing Data Fusion

Hui

2022

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

Based on the specific circumstances of colleges and universities, this study presents the moral education management system and leverages multisource sensor data and other technologies to develop an information system in line with the moral education management of modern college students. Using multisource sensor data fusion and learning data definition, the fused education data is expressed in a standardized way, resulting in a common and standard data interchange format. This foundation is used to build a shareable and reusable data management system that enables data sharing and interchange across multiple heterogeneous data sources, aids the intelligent education system in obtaining more comprehensive and complete recorded data, and improves data sharing timeliness. As a result, learning behavior analysis results are more objective, immediate, and accurate, allowing the intelligent education system’s response to be more prompt and intelligent. This study, which is based on multisource sensor data fusion, also discusses platform selection, system architecture, database design, and methods and suggestions for overcoming critical challenges and can be used as a reference for other university information management systems with vast amounts of data.

show abstract

Section: Analysis Of Multisource Data Fusionmentioning

confidence: 99%

[Retracted] Design of Moral Education Management System for Higher Vocational Students Based on Multisource Sensing Data Fusion

Hui

2022

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

show abstract

“…When a pedestrian moves around a base station with a UWB tag, the tag emits UWB signals periodically. Suppose that moments when BS i (i = 1, 2, 3, 4) receive UWB signals are t i , respectively, then the TDOA equation can be obtained as Equation (1).…”

Section: Description Of the Tdoa Positioning Methodsmentioning

confidence: 99%

“…In recent years, with the rapid development of location-based service (LBS) applications, indoor positioning research in large indoor spaces (such as underground parking lots and large commercial complexes) has received increasing attention from scholars. High-accuracy indoor positioning technology has become a common basis for public safety, intelligent management, business analysis, LBS, and other fields [ 1 ]. At present, many methods are used to build indoor positioning systems, such as the time-based positioning method [ 2 , 3 , 4 ], radio fingerprints [ 5 , 6 , 7 , 8 ], and dead reckoning [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

An Indoor Positioning Method Based on UWB and Visual Fusion

Peng

Xia

et al. 2022

Sensors

View full text Add to dashboard Cite

Continuous positioning and tracking of multi-pedestrian targets is a common concern for large indoor space security, emergency evacuation, location services, and other application areas. Among the sensors used for positioning, the ultra-wide band (UWB) is a critical way to achieve high-precision indoor positioning. However, due to the existence of indoor Non-Line-of-Sight (NLOS) error, a single positioning system can no longer meet the requirement for positioning accuracy. This research aimed to design a high-precision and stable fusion positioning system which is based on the UWB and vision. The method uses the Hungarian algorithm to match the identity of the UWB and vision localization results, and, after successful matching, the fusion localization is performed by the federated Kalman filtering algorithm. In addition, due to the presence of colored noise in indoor positioning data, this paper also proposes a Kalman filtering algorithm based on principal component analysis (PCA). The advantage of this new filtering algorithm is that it does not have to establish the dynamics model of the distribution hypothesis and requires less calculation. The PCA algorithm is firstly used to minimize the correlation of the observables, thus providing a more reasonable Kalman gain by energy estimation and the denoised data, which are substituted into Kalman prediction equations. Experimental results show that the average accuracy of the UWB and visual fusion method is 25.3% higher than that of the UWB. The proposed method can effectively suppress the influence of NLOS error on the positioning accuracy because of the high stability and continuity of visual positioning. Furthermore, compared with the traditional Kalman filtering, the mean square error of the new filtering algorithm is reduced by 31.8%. After using the PCA-Kalman filtering, the colored noise is reduced and the Kalman gain becomes more reasonable, facilitating accurate estimation of the state by the filter.

show abstract

“…The twice correction algorithm, combining linear fitting and polynomial methods, enhances both static and dynamic positioning accuracy [18]. Multi-sensor data fusion techniques, such as integrating UWB with inertial measurement units (IMUs) and encoders, employ Kalman filtering to enhance positioning accuracy by leveraging the complementary strengths of different sensors [19]. Despite improvements, the complexity of sensor integration [20] and the need for extensive calibration [21] can limit these methods.…”

Section: Introductionmentioning

confidence: 99%

System and Method for Reducing NLOS Errors in UWB Indoor Positioning

Wang,

Zhang,

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

The ultra-wideband (UWB) technology has been increasingly recognized as an efficacious strategy for Indoor Positioning Systems (IPSs). However, the accuracy of the UWB system can be severely degraded by non-line-of-sight (NLOS) errors. In this study, we proposed a new method to reduce the UWB positioning error in such an indoor environment. We developed a system consisting of a Robotic Total Station (RTS), four UWB base stations, a moving target (including a prism and a UWB tag), and a PC. The observed coordinates of the moving target, captured using millimeter precision from an RTS device, served as the ground truth for calculating the positioning errors of the UWB tag. In a significant NLOS scenario, the UWB’s three-dimensional positioning error was identified to exceed the nominal value declared by the manufacturer by a factor of more than three. A detailed analysis revealed that each coordinate component’s error distribution pattern demonstrated considerable variance. To reduce the NLOS error, we designed a combined multilayer neural network that simultaneously fits errors on all three coordinate components and three separate multilayer networks, each dedicated to optimizing errors on a single coordinate component. All networks were trained and verified by benchmark errors obtained from the RTS. The results showed that neural networks outperform the traditional methods, attributed to their strong nonlinear modelling ability, thereby significantly improving the external accuracy by an average reduction in RMSE by 61% and 72%. It is evident that the proposed separate networks would be more suitable for NLOS positioning problems than a combined network.

show abstract

Review on UWB-based and multi-sensor fusion positioning algorithms in indoor environment

Cited by 10 publications

References 6 publications

[Retracted] Design of Moral Education Management System for Higher Vocational Students Based on Multisource Sensing Data Fusion

[Retracted] Design of Moral Education Management System for Higher Vocational Students Based on Multisource Sensing Data Fusion

An Indoor Positioning Method Based on UWB and Visual Fusion

System and Method for Reducing NLOS Errors in UWB Indoor Positioning

Contact Info

Product

Resources

About