TOF-Based Fast Self-Positioning Algorithm for UWB Mobile Base Stations

Han, Yuxiang; Zhang, Xiaoming; Lai, Zhengxi; Geng, Yuchen

doi:10.3390/s21196359

Cited by 6 publications

(2 citation statements)

References 16 publications

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“…The analysis shows that the accuracy of the algorithm is closely related to the UWB positioning accuracy that is affected by the measure errors and the position accuracy of the base stations. 27,28 At present, the positioning accuracy has been improved by the researchers, and the simulation error of 2 cm is chosen as the lower limit in this article. 29 We suppose the coordinates of the three base stations are (0,0), (0, 800), and (800, 0); the robot centroid coordinates (400, 400); target point position (800, 800); actual posture angle 45 ; and the installation distance of the two tags 60 cm.…”

Section: Resultsmentioning

confidence: 99%

Posture algorithm for mobile robot based on ultrawide band

Sun

Xie

Xiong

et al. 2022

International Journal of Advanced Robotic Systems

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Inertial measurement unit or other navigation devices are used to obtain the posture information of most mobile robots based on ultrawide band. However, problems, such as zero drift, temperature drift, and error increasing with time, exist in inertial measurement unit and other navigation devices. To overcome these problems, a posture algorithm for mobile robot based on ultrawide band is proposed in this article. Real-time posture information can be obtained by the posture algorithm without using inertial measurement unit and other navigation devices. Simulated results show that the mean absolute error and root mean square error of posture angle in the global coordinate system are 0.951° and 1.169°, respectively. Both the simulated and experimental trajectories show good agreement with the ideal trajectory. The results indicate that the posture data can be obtained accurately by the posture algorithm and the accuracy can meet the requirements for most mobile robots. This article is expected to be of great guiding significance for the development of mobile robots.

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Section: Resultsmentioning

confidence: 99%

Posture algorithm for mobile robot based on ultrawide band

Sun

Xie

Xiong

et al. 2022

International Journal of Advanced Robotic Systems

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show abstract

“…Currently, UWB modes include Time of Arrival (TOA), Time of Flight (TOF), Difference of Time-Of-Arrival (TDOA), Angle of Arrival (AOA), Received Signal Strength Indication (RSSI) [17,18]. TOF is widely used in indoor applications because the tag does not need to be synchronization with the base station precisely [19,20].…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Evaluations of NLOS and Linearization Errors on UWB Positioning

Гао

et al. 2023

Applied Sciences

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Currently, ultra-wide band (UWB) is adopted as a useful high-accuracy positioning technique in satellite-blocked areas. However, UWB’s positioning performance would be limited significantly because of non-line of sight (NLOS) errors. Additionally, the truncation errors in these linearization-based adjustments such as least squares (LS) and extended Kalman filter (EKF) would also visibly degrade UWB positioning accuracy. To overcome the impacts of NLOS errors and truncation errors, this paper introduced a robust-theory-based particle filter (RPF) into UWB positioning. In such a method, the IGG-III model and PF were adopted to limit the impacts of NLOS errors and truncation errors, respectively, by introducing a weight inflation factor and particle group. For comparison, the Bancroft, LS, EKF, unscented Kalman filter (UKF), cubature Kalman filter (CKF), PF, and RPF were also presented. Here, the influences of truncation errors were analyzed by comparing the results based on LS and EKF with those calculated by UKF, CKF, and PF. The impacts of NLOS errors were evaluated by making a comparison between the results of PF and RPF. Results based on a set of simulated UWB data and a group of experiment UWB data demonstrated that the RPF can significantly avoid the positioning errors caused by both truncation errors and NLOS errors. In general, position improvements percentages of 57.2%, 52.7%, 39.6%, 38.2%, 26.6%, and 20.4% can be obtained by RPF compared to those calculated by Bancroft, LS, EKF, UKF, CKF, and PF, respectively. As a comparison, the truncation error would lead to about 8.1%, 10.1%, and 33.2% accuracy decrease in the north, east, and vertical directions on average. Such accuracy-decrease rates caused by NLOS were 6.1%, 5.2%, and 25%.

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Heterogeneous sensing for target tracking: architecture, techniques, applications and challenges

Li²,

Chen³

et al. 2023

Meas. Sci. Technol.

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Target tracking applications are promising, it has great theoretical and practical significance, but the research faces great challenges. With the development of multi-modal depth sensing technology, a large number of scholars have proposed various target tracking methods based on heterogeneous sensing and got great results. This paper provides an overview of the techniques involved in target tracking in the different layers of the network and a comprehensive analysis of the research progress in heterogeneous sensing techniques in each layer. First, this paper introduced the single sensing scheme and heterogeneous sensing scheme in the physical layer. Second, we presented heterogeneous communication technologies and heterogeneous optimization methods for communication protocols in the network layer. Third, we combined several typical heterogeneous sensory target tracking applications and analyzed the application of cloud computing, edge computing, big data, and blockchain technologies. Finally, we discussed the challenges and future direction of heterogeneous sensory target tracking methods.

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TOF-Based Fast Self-Positioning Algorithm for UWB Mobile Base Stations

Cited by 6 publications

References 16 publications

Posture algorithm for mobile robot based on ultrawide band

Posture algorithm for mobile robot based on ultrawide band

Comprehensive Evaluations of NLOS and Linearization Errors on UWB Positioning

Heterogeneous sensing for target tracking: architecture, techniques, applications and challenges

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