The Development and Progress of the UWB Physical Layer

Lv, Ziteng; Chen, Dongdong; Li, Di; Wang, Xianglong; Zhao, Tongtong; Yang, Yanchao; Zhao, Yanbo; Zhang, Xin

doi:10.3390/mi14010008

Cited by 4 publications

(3 citation statements)

References 80 publications

(127 reference statements)

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“…UWB radar realizes the detection, recognition, and imaging of specific targets by emitting and receiving electromagnetic waves [1][2][3]. Compared with common sensors like optical or infrared ones, UWB radar contains certain technical advantages in high resolution, high penetrability, and all-weather, all-time functional capability, receiving wide applications in both civil and martial spheres [4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Two-Step Accuracy Improvement for Multitarget Detection in Complex Environment Using UWB Radar

Liang,

Jin,

Yang

et al. 2024

Remote Sensing

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Detecting multiple human targets in indoor scenarios using ultra-wideband (UWB) radar usually involves false detection results caused by the secondary reflections, which might reduce the target detection accuracy and cause a more severe deterioration when the number of targets increases. This article proposed a two-step accuracy improvement method for multitarget detection in environments with multiple human targets of more than three and strong secondary reflections by the surroundings, especially the walls. Based on the rough detection results acquired by the modified CA-CFAR (MCA-CFAR) processing, the first step achieves the primary false alarm suppression using a short-window accumulation in the time domain. Then, the second step applies the decision confidence on the detection results from the first step to assess the reliability of results for improved accuracy. The two-step accuracy improvement could thus have a higher accuracy through cascading false alarm suppression. The effectiveness and accuracy of the proposed algorithm are verified based on the experimental results.

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Section: Introductionmentioning

confidence: 99%

Two-Step Accuracy Improvement for Multitarget Detection in Complex Environment Using UWB Radar

Liang,

Jin,

Yang

et al. 2024

Remote Sensing

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“…However, the MIMU orientation method is less accurate because it is more subject to ambient interference and mistakes brought on by attitude and position solving from pure inertial guiding data. Where conventional GPS [ 9 ] cannot be used in underground mine environments [ 10 ], UWB [ 11 , 12 ] positioning systems can be used in environments where GPS is denied. SINS has been successfully applied to the positioning of continuous coal mining machines [ 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Research on IMU-Assisted UWB-Based Positioning Algorithm in Underground Coal Mines

Wang

Zhang

et al. 2023

Micromachines

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The application of an ultra-wideband (UWB) positioning system in a Global Positioning System (GPS) denial environment such as an underground coal mine, mainly focuses on position information and rarely involves information such as direction attitude. Position accuracy is often affected by multipath, non-visible ranges, base station layout, and more. We proposed an IMU-assisted UWB-based positioning system for the provision of positioning and orientation services to coal miners in underground mines. The Error-State Kalman Filter (ESKF) is used to filter the errors in the measured data from the IMU-assisted UWB positioning system to obtain the best estimate of the error for the current situation and correct for inaccuracies due to approximations. The base station layout of the IMU-assisted UWB positioning system was also simulated. The reasonable setting of the reference base station location can suppress multi-access interference and improve positioning accuracy to a certain extent. Numerous simulation experiments have been conducted in GPS denial environments, such as underground coal mines. The experimental results show the effectiveness of the method for determining the position, direction, and attitude of the coal miner under the mine, which provides a better reference value for positioning and orientation in a GPS rejection environment such as under the mine.

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“…In general, UWB wireless positioning technology uses pulse signals with extremely low power spectral density and narrow pulse width to transmit data, achieving high time resolution and strong barrier penetration. In a line-of-sight (LOS) environment, centimeter-or even millimeter-level of positioning accuracy can be obtained [5][6][7]. In UWB-based positioning, typical location algorithms are classified as time of arrival (TOA), time differential of arrival (TDOA) [8], time of flight (TOF), received signal strength (RSSI), and angle of arrival (AOA) [9,10].…”

Section: Introductionmentioning

confidence: 99%

Variable-Weighted Error Propagation Model of a Ultra-Wide-Band Indoor Positioning System in an Intelligent Manufacturing Lab

et al. 2023

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Ultra-wide-band (UWB) positioning is a satisfying indoor positioning technology with high accuracy, low transmission cost, high speed, and strong penetration capacity. However, there remains a lack of systematic study on inevitable and stochastic errors caused by factors originating from the multipath effect (ME), non-line-of-sight interference (NLOSI), and atmospheric interference (AI) in UWB indoor positioning systems. To address this technical issue, this study establishes a dynamic error-propagation model (DEPM) by mainly considering the ME, NLOSI, and AI. First, we analyze the UWB-signal generation principle and spread characteristics used in indoor positioning scenarios. Second, quantization models of the ME, NLOSI, and AI error factors are proposed based on data from related studies. Third, to adapt to various environments, we present a variable-weighted DEPM based on the quantization models above. Finally, to validate the proposed dynamic error-propagation model, UWB-based positioning experiments in an intelligent manufacturing lab were designed and conducted in the form of static and dynamic longitude-tag position measurements. The experimental results showed that the main influencing factors were ME and NLOSI, with a weight coefficient of 0.975, and AI, with a weight coefficient of 0.00025. This study proposes a quantization approach to main error factors to enhance the accuracy and precision of indoor UWB-positioning systems used in intelligent manufacturing areas.

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The Development and Progress of the UWB Physical Layer

Cited by 4 publications

References 80 publications

Two-Step Accuracy Improvement for Multitarget Detection in Complex Environment Using UWB Radar

Two-Step Accuracy Improvement for Multitarget Detection in Complex Environment Using UWB Radar

Research on IMU-Assisted UWB-Based Positioning Algorithm in Underground Coal Mines

Variable-Weighted Error Propagation Model of a Ultra-Wide-Band Indoor Positioning System in an Intelligent Manufacturing Lab

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