WUB-IP: A High-Precision UWB Positioning Scheme for Indoor Multiuser Applications

Yin, Zhendong; Xu, Jingdong; Yang, Zhutian; Zhao, Nan; Chen, Yunfei

doi:10.1109/jsyst.2017.2766690

Cited by 69 publications

(34 citation statements)

References 21 publications

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“…To ensure real-time performance, the Gauss-Newton optimization algorithm [17] is utilized to solve (6). Meanwhile as in Fig.4, is stored for subsequent conversion into the location of GP beacon.…”

Section: Flowchart Of Calibration Of Beacon Locationmentioning

confidence: 99%

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A Novel Simultaneous Calibration and Localization Algorithm Framework for Indoor Scenarios

Deng

Liu

et al. 2020

IEEE Access

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Under the navigational process of simultaneous beacon-calibrating and target-positioning, the real-time positioning and calibrating accuracy in indoor scenarios is significantly limited. To solve it, a novel Simultaneous Calibration and Localization (SCAL) algorithm framework for indoor scenarios is proposed. The proposed framework is mainly divided into the Target Localization and Beacon Calibration (TLBC) and the Global Optimization (GO) section: in the TLBC section, under the typical distributed beacon layout, a processing mechanism for synchronously locating the target and calibrating beacons is proposed; in GO section, parallel to TLBC section, a global optimization method based on Geometric Dilution of Precision based on Error-propagation (EGDOP) model is further proposed, and it can utilize the geometric trajectory of target and positioning error of target and beacons to efficiently and simultaneously optimize the positioning of target trajectory and beacons from TLBC section. The numerical simulation results show that the improvement of the GO section on the positioning performance is verified. Compared with the SCAL algorithm based on backward processing with inverse trajectory, the proposed framework has improved the accuracy of target and beacon positioning by 39.06% and 58.01%, respectively, and accuracy of positioning reaches 0.2557m and 0.2437m, respectively, in an actual indoor positioning scene.

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Section: Flowchart Of Calibration Of Beacon Locationmentioning

confidence: 99%

“…Due to the high reliability, precision, portability, and low cost of positioning technologies based on wireless signals (e.g. Wi-Fi [5], Ultra-Wide Band (UWB) [6], Bluetooth [7], etc. ), it is widely used in indoor.…”

Section: Introductionmentioning

confidence: 99%

A Novel Simultaneous Calibration and Localization Algorithm Framework for Indoor Scenarios

Deng

Liu

et al. 2020

IEEE Access

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“…With the emergence of Global Positioning Systems(GPS), the performance of outdoor positioning has become excellent [2]. But the indoor environment is beyond the coverage of GPS [3]. Therefore the technology of indoor positioning has become a focus of research during the past decade.…”

Section: Introductionmentioning

confidence: 99%

Posting Techniques in Indoor Environments Based on Deep Learning for Intelligent Building Lighting System

et al. 2020

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Recently, with the rapid development of society, solutions to reduce energy consumption in the world have attracted a lot of attention, especial electric energy. In this regard, a system that can control light on and off by determining the location of the person to reduce the waste of electricity used in public buildings, called intelligent building lighting system. Following the practical requirements of the intelligent building lighting system, a technique for positioning in indoor environments is proposed, supporting the design of a positioning system based on deep learning and the Cerebellar Model Articulation Controller (CMAC), called Y-CMAC.This technique adopts YOLOv3 (the method in the paper of YOLOv3: An Incremental Improvement) for object detections and makes the coordinate of a person in the image. On the other hand, using CMAC to calculate the actual position of the person in the indoor environment. Moreover, massive surveillance video is used to reduce the cost of equipment and facilitate the promotion of applications. The average positioning error is controlled at around 1m in this paper. INDEX TERMS Intelligent building lighting system, indoor positioning, monitor identification, CMAC, deep learning.

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“…Then the target is at the intersection of all these ellipses [7]. The elliptical location encountered in the multistatic sonar systems has also been considered in the MIMO radar [14][15][16][17][18][19][20], multistatic radar [21][22][23][24][25] and indoor positioning systems [26,27].…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of a Non-Iterative Estimator for Target Location in Multistatic Sonar Systems with Sensor Position Uncertainties

Wang

Yang

et al. 2020

Mathematics

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Target location is the basic application of a multistatic sonar system. Determining the position/velocity vector of a target from the related sonar observations is a nonlinear estimation problem. The presence of possible sensor position uncertainties turns this problem into a more challenging hybrid parameter estimation problem. Conventional gradient-based iterative estimators suffer from the problems of initialization difficulties and local convergence. Even if there is no problem with initialization and convergence, a large computational cost is required in most cases. In view of these drawbacks, we develop a computationally efficient non-iterative position/velocity estimator. The main numerical computation involved is the weighted least squares optimization, which makes the estimator computationally efficient. Parameter transformation, model linearization and two-stage processing are exploited to prevent the estimator from iterative computation. Through performance analysis and experimental verification, we find that the proposed estimator reaches the hybrid Cramér–Rao bound and has linear computational complexity.

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WUB-IP: A High-Precision UWB Positioning Scheme for Indoor Multiuser Applications

Cited by 69 publications

References 21 publications

A Novel Simultaneous Calibration and Localization Algorithm Framework for Indoor Scenarios

A Novel Simultaneous Calibration and Localization Algorithm Framework for Indoor Scenarios

Posting Techniques in Indoor Environments Based on Deep Learning for Intelligent Building Lighting System

Design and Analysis of a Non-Iterative Estimator for Target Location in Multistatic Sonar Systems with Sensor Position Uncertainties

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