UWB Indoor Research Articles

Human Body Impact and Error Correction for Indoor UWB Ranging

Human Body Impact and Error Correction for Indoor UWB Ranging

Application of a long short-term memory neural network algorithm fused with Kalman filter in UWB indoor positioning

Ultra-wideband technology has good anti-interference capabilities and development prospects in indoor positioning. Since ultra-wideband will be affected by random errors in indoor positioning, to exploit the advantages of the Kalman filter (KF) and the long short-term memory (LSTM) network, this paper proposes a long short-term memory neural network algorithm fused with the Kalman filter (KF–LSTM) to improve UWB positioning. First, the ultra-wideband data is processed through KF to weaken the noise in the data, and then the data is fed into the LSTM network for training, and the capability of the LSTM network to process time series features is employed to obtain more accurate label positions. Finally, simulation and measurement results show that the KF–LSTM algorithm achieves 71.31%, 37.28%, and 49.31% higher average positioning accuracy than the back propagation (BP) network, (back propagation network fused with the Kalman filter (KF-BP), and LSTM network algorithms, respectively, and the KF–LSTM algorithm performs more stably. Meanwhile, the more noise the data contains, the more obvious the stability contrast between the four algorithms.

Calibration and Compensation of Anchor Positions for UWB Indoor Localization

Calibration and Compensation of Anchor Positions for UWB Indoor Localization

Modified UKF for accurate indoor UWB multi-target tracking in the context of SαS NLOS model

Modified UKF for accurate indoor UWB multi-target tracking in the context of SαS NLOS model

Modified UKF for Accurate Indoor UWB Multi-Target Tracking in The Context of SS NLOS Model

Modified UKF for Accurate Indoor UWB Multi-Target Tracking in The Context of SS NLOS Model

A review of UWB indoor positioning

With the development of science and technology, more accurate and stable location information can better serve people’s lives. As people spend more time indoors, traditional positioning technologies such as Wi-Fi can no longer meet their needs due to a lack of positioning accuracy and interference resistance. UWB is an emerging positioning technology with high accuracy, robustness, and stability. This paper compares the advantages and disadvantages of UWB technology with those of Bluetooth and Wi-Fi. Common UWB geometric positioning methods such as TOA, TDOA, etc. are introduced. By introducing the latest research progress in UWB indoor positioning, an outlook on the future development of UWB indoor positioning is made. Compared with Bluetooth and other indoor positioning technologies, UWB positioning technology has the advantages of high positioning accuracy and good anti-interference. The UWB positioning system usually uses TOA, TDOA, AOA, and other positioning algorithms. In the future, UWB positioning technology will serve more and more complex positioning environments.

LOS와 N-LOS 환경에서 측량장비를 활용한 UWB 실내 위치 검증 및 정확도 분석

LOS와 N-LOS 환경에서 측량장비를 활용한 UWB 실내 위치 검증 및 정확도 분석

Improved Indoor Positioning Model Based on UWB/IMU Tight Combination with Double-Loop Cumulative Error Estimation

With the increasing applications of UWB indoor positioning technologies in industrial areas, to further enhance the positioning precision, the UWB/IMU combination method (UICM) has been considered as one of the most effective solutions to reduce non-line-of-sight (NLOS) errors. However, most conversional UICMs suffer from a high probability of positioning failure due to uncontrollable and cumulative errors from inertial measuring units (IMU). Hence, to address this issue, we improved the extended Kalman filter (EKF) algorithm of an indoor positioning model based on UWB/IMU tight combination with a double-loop error self-correction. Compared with conventional UICMs, this improved model consists of new modules for fixing time desynchronization, optimizing the threshold setting for UWB ranging, data fusion in NLOS, and double-loop error estimation, sequentially. Further, systematic error controllability analysis proved that the proposed model could satisfy the controllability of UWB indoor positioning systems. To validate this improved UICM, inevitable obstacles and atmospheric interferences were regarded as Gaussian white noises to verify its environmental adaptability. Finally, the experimental results showed that this proposed model outperformed the state-of-the-art UWB-based positioning models with a maximum deviation of 0.232 m (reduced by 83.93% compared to a pure UWB model and 43.14% compared to the conventional UWB/IMU model) and standard deviation of 0.09981 m (reduced by 88.35% compared to a pure UWB model and 22.21% compared to the conventional UWB-IMU model).

Analysis of UWB Indoor Positioning Accuracy Based on TW-TOF

UWB has the characteristics of low power consumption, low system complexity, strong anti-interference, high penetration, and high positioning accuracy. In this paper, the principle of ultra-wide-band ranging and positioning is introduced in detail, followed by the TOA positioning method based on two-way time-of-flight ranging, and the positioning results are solved by using the least-squares and Gauss-Newton iterative algorithms, and the experimental positioning The experimental positioning errors were analyzed. The experimental results show that UWB has good indoor ranging and positioning accuracy.

Design of Octagon Monopole Dual Frequency Indoor Positioning Beacon Antenna

Aiming at the antenna performance requirements of Bluetooth and UWB indoor positioning system, an octagon monopole dual-frequency indoor positioning beacon antenna is made. The antenna can operate in both UWB and Bluetooth communication bands. The antenna performance is improved by grooving the antenna and adding metal strips. The use of curved and gradual structure feeders also makes the antenna get better bandwidth performance.

산업현장에서의 실내외 연속측위를 위한 GNSS-UWB 하이브리드 측위 시스템

In this paper, we propose a GNSS-UWB hybrid positioning system for indoor and outdoor seamless positioning. Fusion of GNSS and inertial sensors has been widely used as a method for estimating positions in places where GNSS reception sensitivity is low, and UWB technology, which started as a short-range wireless communication technology, is widely used indoors where GNSS is completely blocked. This paper proposes a method of mutual correction and fusion of the location information collected through GNSS and the location information collected from the UWB indoor positioning system when indoor and outdoor work occurs continuously and repeatedly, such as in an industrial site.

Research on UWB Indoor Positioning System Based on TOF Combined Residual Weighting.

The performance of TDOA positioning based on UWB is limited by the hyperbolic characteristics of TDOA, especially for tags away from the hyperbolic asymptote. Aiming at this problem, a new UWB indoor positioning system is proposed. Firstly, TOF ranging is adopted to build the positioning equations; then the weighted centroid algorithm of four base stations is presented to compute the initial rough position of the tag; and the residual weighting is introduced to optimize the initial tag position; then, the corresponding nonlinear positioning equations, which will be algebraically transformed to one distribution function, are solved, and the optimal tag coordinates can be obtained by the Newton iteration method. Simulation experiments have verified the positioning reliability of the proposed algorithm under different noise environments and for different tag positions.

UWB-Based Indoor Positioning System With Infinite Scalability

The ultra-wide band radio technology (UWB) is currently considered the de-facto standard for implementing precise indoor positioning systems. Several positioning algorithms are currently being investigated for finding the best implementation in terms of scalability, refresh rate, and energy requirements. Among all the proposed approaches, the Downlink Time Difference of Arrival (DTDoA) is currently considered one of the most promising techniques capable of tracking any number of assets without decreasing the measurement update rate. This paper proposes a model for the DTDoA and validates the algorithms on UWB data, using a motion capture system as ground truth. Results highlight the validity of the previously proposed model, showing that the proposed UWB indoor positioning system achieves a maximum 30 cm uncertainty with only a simple wireless synchronisation, avoiding wired procedure that limits the usability of the infrastructure.

Efficient Deployment of UWB Anchors for Wide-Area Positioning Coverage Using Bipartite Graph

Indoor mobile robots have been developed rigorously, with more diversified functions and wide applications. The research of indoor robot positioning systems is increasingly critical, and UWB is one of the most accurate methods. However, due to its short reception range, current UWB systems are limited to small activity spaces. Two important questions must be answered to enable UWB systems to be used in a wider area. How many anchors does it need? Where to deploy these anchors? For the first time, this study converts the problem of deploying anchors into finding an ensemble of bipartite graphs. The problem is an np-hard problem, which will be addressed in the study. Nevertheless, the study presents a systematic approach to efficiently solving the number and placement of UWB anchors. The generalized method applies to all places where UWB anchors can be deployed, regardless of spatial shape or size constraints. Moreover, a systematic approach can be used when the total number of UWB anchors is limited; the process can find where to place the anchors so that the robot can be positioned within the maximum range. This method enables the UWB indoor positioning system to be widely and efficiently applied in more fields. Experiments were also conducted to verify the feasibility of this method.

A Novel UWB Positioning Method Based on a Maximum-Correntropy Unscented Kalman Filter

Aiming at the problem of measurement-information abnormal-error and nonlinear filtering in UWB navigation and positioning, an ultra wideband position algorithm based on a maximum cross-correlation entropy unscented Kalman filter is proposed. The algorithm first obtains the predictive state estimate and the covariance matrix through traceless transformation. Then, it reconstructs observation information using the nonlinear regression method based on the maximum cross-correlation entropy criterion, which enhances the robustness of the unscented Kalman filter algorithm for heavy-tailed noise. The simulation and actual test results show that this algorithm has better positioning accuracy and stability than the traditional filter algorithm in a non Gaussian noise environment. This algorithm effectively solves the problem that UWB indoor location is easily affected by indoor environments, resulting in fixed deviation for that location.

UWB Indoor Radio Propagation Modelling in Presence of Human Body Shadowing Using Ray Tracing Technique

This paper presents a ray-tracing method for modelingUltra Wide Bandwidth indoor propagation channels. Avalidation of the ray tracing model with our indoor measurementis also presented. Based on the validated model, the multipathchannel parameter like the fading statistics and root mean squarerms delay spread for Ultra Wide bandwidth frequencies aresimply extracted. The proposed ray-tracing method is basedon image method. This is used to predict the propagation ofUWB electromagnetic waves. First, we have obtained that thefading statistics can be well fitted by log normal distributionin static case. Second, as in realistic environment we cannotneglect the significant impact of Human Body Shadowing andother objects in motion on indoor UWB propagation channel.Hence, our proposed model allows a simulation of propagationin a dynamic indoor environment. Results of the simulation showthat this tool gives results in agreement with those reported inthe literature. Specially, the effects of people motion on temporalchannel properties. Other features of this approach also areoutlined.

Calibration of antenna delays in UWB indoor navigation systems

Calibration of antenna delays in UWB indoor navigation systems

Research on Indoor UWB Positioning Based on Expectation Maximization in NLOS Environment

SummaryUltra‐wide band (UWB) technology is especially suitable for indoor positioning because of its strong anti‐interference ability, it can achieve centimeter‐level positioning accuracy in the line of sight (LOS) environment, but it is challenging to construct a robust and high‐precision algorithm in indoor complex and changeable environments. Therefore, it establishes an improved standard Kalman filter (SKF) based on expectation maximization (SKF‐EM), which models the prediction error covariance and measurement noise using the maximum likelihood criterion, estimates the filter parameters online through the expectation maximum theory, and updates the Kalman filter gain according to the Kalman filter based on dropped measurements method (SKF‐DMM). Experimental results show that: in case of serious occlusion, the maximum positioning error of SKF‐EM algorithm is 1.03 m, 39% lower than that of SKF and 60.2% lower than that of UWB.

College Physical Education Course Management System Based on Internet of Things

With the continuous development of the Internet of Things technology, the latest information technology represented by the network, digital, and intelligence is changing people’s work, learning, and lifestyle and bringing new development space to education. The physical education curriculum management system in colleges and universities brings convenience to teachers and students, facilitates the centralized management of students by teachers, ensures the safety of students in physical education classes, and reduces the risk of injury to students in physical education classes. The innovative construction of college physical education curriculum is a systematic project, which aims to deepen educational reform, improve the physical condition of students, and enable students to experience advanced teaching methods. At the same time, university physical education teachers have a degree of higher education, provide information, and promote interaction with students. This improves the quality and ability of teachers and students themselves. The paper proposes related research on the design of college physical education curriculum management system based on the Internet of Things. Through the use of Internet of Things wireless channel technology and UWB indoor positioning technology, combined with the impact of the Internet of Things on cognition, the arrangement of physical education courses and student positioning and sign-in are designed, and the results of the system test are found. Compared with the previous system,. this system has improved the positioning and sign-in accuracy of physical education courses by 5–10%, and the efficiency of physical education courses has also increased by 2–5%.

UWB positioning algorithm and accuracy evaluation for different indoor scenes

ABSTRACT UWB indoor positioning is a research hotspot, but there are few literatures systematically describing different positioning algorithms for different scenes. Therefore, several positioning algorithms are proposed for different indoor scenes. Firstly, for the sensing positioning scenes, a sensing positioning algorithm is proposed. Secondly, for the straight and narrow scenes, a two anchors robust positioning algorithm based on high pass filter is proposed. Experimental results show that this algorithm has better positioning accuracy and robustness than the traditional algorithm. Then, for ordinary indoor scenes, a robust indoor positioning model is proposed based on robust Kalman filter and total LS, which considers the coordinate error of UWB anchors. The positioning accuracy is 0.093m, which is about 29.54% higher than that of the traditional LS algorithm. Finally, for indoor scenes with map information, a map aided indoor positioning algorithm is proposed based on two UWB anchors. This algorithm can effectively improve the reliability and reduce the cost of UWB indoor positioning system, which average positioning accuracy is 0.238m. The biggest innovation of this paper lies in the systematic description of multi-scene positioning algorithm and the realisation of indoor positioning based on double anchors.