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Currently, with the intensification of global education competition, how to cultivate innovative and versatile talents has become the focus of education today. Informal learning spaces (ILS) have received widespread attention due to their benefits for interdisciplinary interaction. Many forms of ILS have been built, and coffee shops are one of them. However, there is no uniform standard for the design of cafes as ILS, and there are many problems with the spatial quality. This study took a university cafe as a case study and conducted research on the environmental quality and influencing factors from the perspective of environmental behavior. In terms of research methods, this study adopted a combination of ultra-wideband positioning, questionnaire surveys, and environmental data measurements. This research method could obtain the complete relationship between user behavior, time, and location, which improved the shortcomings of traditional research methods of fragmented and accidental data acquisition, and helped to obtain more accurate research results. The study identified the impact proportions of four criteria layer elements and 26 scheme layer factors, which was also the main contribution of this study. In terms of four criteria layer elements, the physical elements had the highest proportion, accounting for 32.46%. The ontology elements ranked second, accounting for 27.07%. The atmosphere elements ranked third, accounting for 24.19%. Finally, facility elements accounted for 16.29%. The top three scheme layer factors were equipment and facilities, noise, and illumination, with weights of 11.18%, 10.71%, and 8.35%, respectively. The study summarized the development directions of cafes as ILS, such as considering the learning needs of different groups, installing sound-absorbing and soundproof devices, adding grilles to external windows, and improving glare problems. [ABSTRACT FROM AUTHOR]

Due to signal shielding caused by building structures, conventional mature positioning technologies such as the Global Positioning System (GPS) are only suitable for outdoor navigation and detection. However, there are many scenarios that urgently require high-precision indoor positioning technologies, such as indoor wireless optical communications (OWCs), navigation in large buildings, and warehouse management. Here, we proposed a millimeter-precision indoor positioning technology based on metalens-integrated camera, which determines the position of the device through imaging of beacon LEDs. Thanks to the wide-angle imaging design of our metalens, the camera can accurately capture images of beacon LEDs even when it is situated in distant corner locations. Consequently, our localization scheme achieves millimeter-level positioning accuracy across majority of wide-angle (∼120°) indoor area. Compared to traditional positioning schemes by photodiode (PD), our imaging-based approach demonstrates superior resistance to interference, thereby safeguarding positioning precision from the external signals influence. Furthermore, the compact dimensions and high performances of the positioning device make it suitable for integration into highly portable devices, such as smartphones and drones, revealing its broad potential applications in the future. [ABSTRACT FROM AUTHOR]

An efficient obstacle detection system is one of the most important guarantees for improving the active safety performance of autonomous vehicles. This paper proposes an obstacle detection method based on high-precision positioning applied to blocked zones to solve the problems of the high complexity of detection results, low computational efficiency, and high load in traditional obstacle detection methods. Firstly, an NDT registration method which uses the likelihood function as the optimal value of the registration score function to calculate the registration parameters is designed to match the scanning point cloud and the target point cloud. Secondly, a target reduction method combined with threshold judgment and the binary tree search algorithm is designed to filter the point cloud of non-road obstacles to improve the processing speed of the computing platform. Meanwhile, KD-tree is used to speed up the clustering process. Finally, a vehicle remote control simulation platform with the combination of a cloud platform and mobile terminal is designed to verify the effectiveness of the strategy in practical application. The results prove that the proposed obstacle detection method can improve the efficiency and accuracy of detection. [ABSTRACT FROM AUTHOR]

Pseudo-satellite technology has excellent compatibility with the BDS satellite navigation system in terms of signal systems. It can serve as a stable and reliable positioning signal source in signal-blocking environments. User terminals can achieve continuous high-precision positioning both indoors and outdoors without any modification to the navigation module. As a result, pseudo-satellite indoor positioning has gradually emerged as a research hotspot in the field. However, due to the complex and variable indoor radio propagation environment, signal propagation is interfered with by noise, multipath, non-line-of-sight (NLOS) propagation, etc. The geometric relation-based localization algorithm cannot be applied in indoor non-line-of-sight environments. Therefore, this paper proposes a pseudo-satellite fingerprint localization method based on the discriminative deep belief networks (DDBNs). The method acquires the model parameters of pseudo-satellite multi-carrier noise density signal strength in non-line-of-sight indoor spaces through a greedy unsupervised learning method and gradient descent-supervised learning method. It establishes a mapping relationship between the implied features of the pseudo-satellite multi-carrier noise density signal strength and indoor location, enabling pseudo-satellite fingerprint matching localization in indoor non-line-of-sight environments. In this paper, the performance of the positioning algorithm is verified in dynamic and static scenarios through numerous experiments in a laboratory environment. Compared to the commonly used localization algorithms based on fingerprint library matching, the results demonstrate that, in indoor non-line-of-sight test conditions, the system's 2D static positioning has a maximum error of less than 0.24 m, an RMSE better than 0.12 m, and a 2σ (95.4%) positioning error better than 0.19 m. For 2D dynamic positioning, the maximum error is less than 0.36 m, the average error is 0.23 m, and the 2σ positioning error is better than 0.26 m. These results effectively tackle the challenge of pseudo-satellite indoor positioning in non-line-of-sight environments. [ABSTRACT FROM AUTHOR]

In recent years, smartphones have emerged as the primary terminal for navigation and location services among mass users, owing to their universality, portability, and affordability. However, the highly integrated antenna design within smartphones inevitably introduces interference from internal signal sources, leading to a misalignment between the antenna phase center (APC) and the antenna geometric center. Accurately determining a smartphone's APC can mitigate system errors and enhance positioning accuracy, thereby meeting the increasing demand for precise and reliable user positioning. This paper delves into a detailed analysis of the generation of Global Navigation Satellite System (GNSS) receiver antenna phase center errors and proposes a method for correcting the receiver antenna phase center. Subsequently, a smartphone positioning experiment was conducted by placing the smartphone on an observation column with known coordinates. The collected observations were processed in static relative positioning mode, referencing observations from geodetic-grade equipment, and the accuracy of the static relative positioning fixed solution was evaluated. Following weighted estimation, we determined the antenna phase center of the Xiaomi Mi8 and corrected the APC. A comparison of the positioning results of the Xiaomi Mi8 before and after APC correction revealed minimal impact on the standard deviations (STDs) but significant influence on the root mean square errors (RMSEs). Specifically, the RMSEs in the E/N/U direction were reduced by 59.6%, 58.5%, and 42.0%, respectively, after APC correction compared to before correction. Furthermore, the integer ambiguity fixing rate slightly improved after the APC correction. In conclusion, the determination of a smartphone's APC can effectively reduce system errors in the plane direction of GNSS positioning, thereby enhancing smartphone positioning accuracy. This research holds significant value for advancing high-precision positioning studies related to smartphones. [ABSTRACT FROM AUTHOR]

This paper proposed a feedforward-feedback (FF-FB) control strategy for a linear piezoelectric walking stage (LPWS) based on the parameter-dependent Bouc-Wen (PD-BW) model under condition variations. The mathematical model of LPWS is established by linearization, which consists of a linear system and a hysteresis nonlinearity system. The linear dynamics model of LPWS is identified by the swept-sine method, whereas the hysteresis nonlinearity model of LPWS is identified based on the PD-BW model. The feedforward controller based on the inverse PD-BW model can compensate for the inherent hysteresis nonlinearity of LPWS at varying excitation frequency, surrounding temperature, and external load. A proportional plus lead-lag feedback controller is built to reduce feedforward modelling error and improve the output accuracy of LPWS. The sensitivity analysis of the LPWS feedback control system is performed to reduce the effect of disturbance and noise. Experimental results present the feasibility and effectiveness of the proposed FF-FB control strategy to achieve an efficient and accurate positioning performance. • A feedforward-feedback control method based on the parameter-dependent Bouc-Wen model is applied to a piezoelectric stage. • The proposed parameter-dependent Bouc-Wen model compensates for the hysteresis of piezoelectric actuators under varying conditions. • The sensitivity analysis is performed to achieve accurate output performance and suppress disturbance and noise. [ABSTRACT FROM AUTHOR]

Copyright of Railway Investigation & Surveying is the property of Railway Investigation & Surveying Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Currently, with the intensification of global education competition, how to cultivate innovative and versatile talents has become the focus of education today. Informal learning spaces (ILS) have received widespread attention due to their benefits for interdisciplinary interaction. Many forms of ILS have been built, and coffee shops are one of them. However, there is no uniform standard for the design of cafes as ILS, and there are many problems with the spatial quality. This study took a university cafe as a case study and conducted research on the environmental quality and influencing factors from the perspective of environmental behavior. In terms of research methods, this study adopted a combination of ultra-wideband positioning, questionnaire surveys, and environmental data measurements. This research method could obtain the complete relationship between user behavior, time, and location, which improved the shortcomings of traditional research methods of fragmented and accidental data acquisition, and helped to obtain more accurate research results. The study identified the impact proportions of four criteria layer elements and 26 scheme layer factors, which was also the main contribution of this study. In terms of four criteria layer elements, the physical elements had the highest proportion, accounting for 32.46%. The ontology elements ranked second, accounting for 27.07%. The atmosphere elements ranked third, accounting for 24.19%. Finally, facility elements accounted for 16.29%. The top three scheme layer factors were equipment and facilities, noise, and illumination, with weights of 11.18%, 10.71%, and 8.35%, respectively. The study summarized the development directions of cafes as ILS, such as considering the learning needs of different groups, installing sound-absorbing and soundproof devices, adding grilles to external windows, and improving glare problems.

Outdoor substation is an important part of power system. Substation inspection robot based on intelligent autonomous inspection system has become the research focus of substation unmanned inspection. In order to improve the positioning accuracy and speed of the system, a high-precision positioning algorithm of transformer detection robot is proposed in this paper. Tikhonov regularization is used to correct the pathological problem of the localization algorithm model. The observation amount of the receiver is increased by using four signals of a single base station with double frequency and double antenna, and the position is solved by using single difference carrier phase observation and the integer ambiguity is fixed. The input–output mapping of the neural network is designed according to the information acquisition and two-wheel angular velocity control of the detection robot. Using the hyperbolic tangent function as the activation function of MLP neural network, the MLP neural network with 32 neurons in each of the three hidden layers is determined. By optimizing reinforcement learning reward function, adding scoring rules, and reward parameters, this paper carries out the following simulation exploration work. The high-precision positioning algorithm of transformer inspection robot is compared with the existing algorithm, and the superiority of the algorithm is verified. The basic motion ability of the robot installed with the system was tested. [ABSTRACT FROM AUTHOR]

A macro–micro dual-drive positioning system was developed for Scanning Beam Interference Lithography (SBIL) which uses a dual-frequency laser interferometer as the position reference and exhibits the characteristics of long travel, heavy load, and high accuracy. The macro-motion system adopts a friction-driven structure and a feedforward PID control algorithm, and the stroke can reach 1800 mm. The micro-motion system adopts a flexible hinge–plus-PZT driving method and a PID control algorithm based on neural networks, which achieves sufficient positioning accuracy of this system at the nanometer level. An optical-path-sealing system was used to reduce the measurement noise of the dual-frequency laser interferometer. The static stability of the positioning system, the stepping capacity of the macro-motion system, the stepping capacity of the micro-motion system, and the positioning accuracy of the system were tested and analyzed. Additionally, the sources and effects of errors during the motion process were assessed in detail. Finally, the experimental results show that the workbench can locate at the nanoscale within the full range of travel, which can satisfy the SBIL exposure requirement. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

High-precision global navigation satellite system (GNSS) positioning technology, as a hot spot in the field of satellite navigation, has expanded the in-depth development of the location-based service area, and has been widely used in smart cities, intelligent transportation, autonomous driving and other fields. First, this paper presents the current status and development of GNSS positioning technologies.Then, it explains the common basic theories such as integer ambiguity fixation, functional model and stochastic model fusion involved in multi-frequency multi-GNSS high-precision positioning, as well as the key techniques for improving GNSS positioning performance such as the non-model error processing, the cycle slip detection and data interruption repair. Based on the innovations of basic theories and key techniques, this paper introduces four new technologies for multi-frequency multi-GNSS high-precision positioning applications developed by Tongji University GNSS team in recent years. Finally, we remark the future development trend and challenges of GNSS-based high-precision positioning. [ABSTRACT FROM AUTHOR]

An efficient obstacle detection system is one of the most important guarantees for improving the active safety performance of autonomous vehicles. This paper proposes an obstacle detection method based on high-precision positioning applied to blocked zones to solve the problems of the high complexity of detection results, low computational efficiency, and high load in traditional obstacle detection methods. Firstly, an NDT registration method which uses the likelihood function as the optimal value of the registration score function to calculate the registration parameters is designed to match the scanning point cloud and the target point cloud. Secondly, a target reduction method combined with threshold judgment and the binary tree search algorithm is designed to filter the point cloud of non-road obstacles to improve the processing speed of the computing platform. Meanwhile, KD-tree is used to speed up the clustering process. Finally, a vehicle remote control simulation platform with the combination of a cloud platform and mobile terminal is designed to verify the effectiveness of the strategy in practical application. The results prove that the proposed obstacle detection method can improve the efficiency and accuracy of detection.

In this article, a finite-time controller is designed on high-precision positioning for an inertial reference unit (IRU) with asymmetric loads and mover sideslip based on a finite-time extended state observer (ESO). The asymmetric loads caused by centroid deviation from central axis are a negative factor, which results in a negative load torque for IRUs. The mover sideslip is another negative factor that brings about output forces errors between actual output forces and theoretical output forces for voice coil motors. The finite-time ESO is designed to estimate and compensate the asymmetric loads and mover sideslip. The finite-time controller is proposed with high convergence rate for the IRU. Experimental results are presented to show effectiveness of the proposed finite-time control method in high-precision positioning under asymmetric loads and mover sideslip. [ABSTRACT FROM AUTHOR]

In recent years, unmanned surface vessels have played a vital role in Antarctic scientific research missions, especially in Antarctic ocean surveys and port surveillance. High-precision positioning technology is essential to ensure reliable autonomous navigation of unmanned ships in Antarctic navigation and operations. Carrier positioning is the main technology for high-precision positioning, but factors such as signal interruption and geographical environment can cause the GNSS receiver to lose lock, causing cycle slips in the carrier phase. If the carrier phase with cycle slip is used for positioning solution, serious positioning errors will occur. Effective processing of cycle slips can result in cleaner carrier phase data, help fix ambiguities and improve accuracy. This paper proposes a smooth Doppler-aided phase pseudo-range cycle slip detection method to reduce the impact of observation noise and improve detection accuracy. For manually added cycle slips, the detection success rate reaches 100%. In the dynamic Antarctic experiment, in PPP mode, the root mean square values in the E, U, and N directions are 0.055 m, 0.034 m, and 0.037 m respectively, reaching centimeter-level accuracy. This research is of great significance for high-precision positioning applications in Antarctica. • A smoothed Doppler-aided phase pseudo-range cycle slip detection method is proposed to improve the detection accuracy. • The effects of observation noise can be greatly reduced by using the proposed method. • The proposed method proves to have excellent performance in Antarctic navigation experiments. [ABSTRACT FROM AUTHOR]

In order to improve the safe driving and automatic positioning capability of autonomous vehicles, a high-precision DSRC and LiDAR data integration positioning technology for autonomous vehicles based on CNN is proposed. Import the data of Dedicated Short Range Communications and Light Detection and Ranging for automatic driving vehicle positioning, carry out kinematic analysis of autonomous driving vehicles under multi-sensor fusion, and transform the data of DSRC and LiDAR sensors into tightly coupled coordinate systems; The CNN depth learning method is used to compensate the position and attitude tracking estimation error under the overall time stamp synchronization of the sensor through adaptive information tracking; The first and second order feedforward compensation is made for the positioning parameters of the autonomous driving vehicle using the PID model, and the point cloud feature matching model is fused to complete the estimation of the positioning attitude parameters of the autonomous driving vehicle. In order to eliminate the noise interference under the DSRC communication mechanism, the Kalman filter function is used to automatically optimize the constraint parameters in the point cloud feature detection model, and the positioning error parameters are dynamically filtered and adjusted; Kinematics analysis is carried out for the driving state of the vehicle, and the positioning error in the vehicle movement is controlled through the difference technology to achieve high-precision DSRC and LiDAR data integration positioning. The simulation results show that this method can integrate and locate the high-precision DSRC and LiDAR data of the autonomous vehicle, and the attitude estimation and positioning accuracy of the vehicle is good, while the error of the attitude parameter estimation of the autonomous vehicle is low. [ABSTRACT FROM AUTHOR]

In contrast to outdoor environments, indoor positioning encounters signal propagation disruptions due to the presence of buildings, resulting in reduced accuracy and, at times, the inability to determine a location accurately. This research, leveraging the robust penetrative capabilities of Ultra-Wideband (UWB) signals in non-line-of-sight (NLOS) scenarios, introduces a methodology for refining ranging outcomes through a combination of inertial navigation and environmental adjustments to achieve high-precision spatial positioning. This approach systematically enhances the correction of signal propagation errors through walls. Initially, it digitalizes the spatial setting, preserving the error correction parameters. Subsequently, it employs inertial navigation to estimate spatial coordinates and delineate signal propagation pathways to achieve precise ranging results. It iteratively hones the positioning outcomes for enhanced precision. Empirical findings demonstrate that within NLOS conditions, compared to standalone UWB positioning and IMU/UWB fusion positioning using the ESKF algorithm, this positioning technique significantly enhances planar positioning accuracy while achieving a marginal elevation accuracy improvement, albeit with some residual deviations from actual values. Furthermore, this positioning methodology effectively rectifies results in NOLS settings, paving the way for a novel approach to optimize indoor positioning through UWB technology.

Positioning is not only the cornerstone of ensuring the safe driving of vehicles, but also the foundation of many location-related services.The development and application of the positioning technology have greatly affected the development prospects of the Internet of vehicles.Mobile edge computing can migrate intensive computing tasks to the edge of the network adjacent to the car or roadside.By sinking the computing power to the edge of the network, mobile edge computing can offload the load of network transmission, save the transmission bandwidth, and support Internet of vehicles applications powerfully.It was aimed to study the integration of MEC and IoV positioning technology, and form the overall architecture of MEC-based positioning technology by analyzing the application scenarios and integration requirements of MEC integrated positioning technology in IoV.At the same time, the opportunities and challenges of the architecture were further analyzed to provide an important reference for the subsequent standardization of MEC-based positioning technology and the application in the Internet of vehicles.

BeiDou high-precision power line inspection can improve the efficiency and automation level of inspection operations, reduce labor intensity, and save inspection costs. However, although the satellite-based augmentation technology can solve the problem of large-scale positioning, it will introduce too many parameters into the positioning system through the method of parameter estimation. As a result, the behavior of the equation deteriorates, which makes it difficult to separate some parameters, and the convergence time of ambiguity parameters is too long. Under normal circumstances, the satellite-based augmentation standard positioning service needs at least about 30 min to converge to the centimeter level, and the ground-based augmentation system can provide an accurate model. This paper proposes a fast positioning method for satellite-based augmentation assisted by the BeiDou ground-based augmentation station. The receiver adopts the least square method, combined with the extended Kalman filter positioning, to achieve the improvement of the regional positioning effect of the satellite-based augmentation system. Positioning accuracy error does not exceed 1.6 meters. The error in the three directions of X, Y, and Z can be converged to the centimeter level in about 8 min. It can significantly improve the convergence time of satellite-based augmentation, and maintain continuous, stable and high-precision positioning of unmanned aerial vehicle in power line inspection.

High-precision indoor positioning technology is of great significance to the development of national economy. In recent years, with the increasing demand for location services and the continuous iteration of technology, indoor positioning continues to develop towards high precision and seamless. In the case that the satellite signal cannot cover the indoor, the high-precision indoor positioning technology has become a research hotspot, and a variety of positioning sources and corresponding positioning principles have been developed. Aiming at the latest development status of high-precision indoor positioning technology, we divide into high-precision positioning methods based on geometric relation, fingerprint matching, incremental estimation and quantum navigation according to different positioning principles. We introduce the positioning principle of various methods, discuss and analyze the current technology development, summary the characteristics of high-precision indoor positioning technology, and discuss the future development trend of multi-source, intelligent and popular. Through the analysis of different positioning principles and technologies, it has reference value for the future study of indoor high-precision positioning sources and fusion positioning methods of different positioning sources. [ABSTRACT FROM AUTHOR]

Location-based services (LBSs) provide necessary infrastructure for daily life, from bicycle sharing to nursing care. In contrast to traditional positioning methods such as Wi-Fi, Bluetooth, and ultra-wideband (UWB), fifth-generation (5G) networking is defined as a paradigm of integrated sensing and communication (ISAC). With its advantages of wide-range coverage and indoor-outdoor integration, 5G is promising for high-precision positioning in indoor and urban canyon environments. However, 5G location studies face great obstacles due to the lack of commercialized 5G ISAC base stations that support positioning functions as well as publicly available datasets. In this paper, we first propose a dataset generation method, the Multilevel Feature Synthesis Method (Multilevel-FSM), to obtain positioning features. In particular, the features of a multiple-input multiple-output (MIMO) channel are flattened into a single image to increase the information density and improve feature expression, and data augmentation is performed to provide stronger robustness to noise. Subsequently, we devise a specially designed deep learning positioning method, Multipath Res-Inception (MPRI), trained on the proposed dataset to enhance positioning accuracy. Finally, the results of extensive experiments conducted in two typical 5G scenarios (indoors and urban canyon) show that Multilevel-FSM and MPRI outperform state-of-the-art works in accuracy, time overhead and robustness to noise. [ABSTRACT FROM AUTHOR]

Global navigation satellite system (GNSS) plays a vital role in high-precision positioning whereas detecting and mitigating carrier phase multipath error is still a significant challenge. Multipath error is closely related to the users’ environment, so it is difficult to mitigate by traditional differencing techniques. In this paper, we discuss the possibility and potential performance of multipath detection and mitigation with low-cost antennas in real-time kinematic (RTK) positioning. We employ two low-cost antennas and assume that the baseline length is known. We employ the carrier phase, ephemeris, and baseline length to detect the observed and estimated baseline vectors’ consistency in real-time. A reasonable threshold is proposed to detect the satellite signals with the multipath effect, then we eliminate these signals and use the remaining satellite signals for RTK positioning to mitigate multipath. The experiments are carried out in the open environment without multipath and the environment with specular multipath. Experimental results show that the false alarm rate of this method is entirely consistent with the theoretical value. When the number of satellites is six and eight, this method can reduce the RMS (root mean square) of positioning error by approximately 64% and 49%, respectively. At the same time, this method can improve the ambiguity success rate to above 99%. [ABSTRACT FROM AUTHOR]

Nowadays, the autonomous vehicle has undergone an impressive development, in which one of the most challenging tasks is to pursue high-precision and continuous navigation in complex scenarios. However, GNSS signals are very likely to be blocked and the inertial system suffers from error drift over time. To achieve centimeter-level positioning accuracy, a tightly-coupled model is built via fusing visual, GNSS, and INS measurements, based on a priori visual feature map. The visual map is first generated by a visual mobile surveying system, and the quality of the map is improved by outlier elimination and road lane tracking. This visual feature map consists of two layers that involve 3D coordinates of robust visual features and road lane markings, then two GNSS/INS/Vision fusion models are developed. The first one fuses visual 2D-3D feature matching, GNSS, and INS measurement. The proposed system is effective even when satellites are all out of lock. The second one fuses lane line constraints with GNSS, INS, and distance measurement indicator (DMI). In the experiment part, we show how a visual feature map is generated and refined, then, the performance of the positioning algorithm is evaluated. For the first fusion model, we achieve 10 cm RMS accuracy when only one feature point was matched and all GNSS signals are blocked for 20 minutes. For the other fusion model, the system maintained 10 cm RMS accuracy or even better when a few GNSS satellites are out of lock for 300 seconds. [ABSTRACT FROM AUTHOR]

To improve positioning precision of the traveling wave ultrasonic motor (USM), a flexible shaft was used, and the structure was redesigned to reduce the fluctuations of step angles and speed. The start and stop response performances of the motor were analyzed theoretically and tested by a high-resolution test rig. The step characteristics were calculated, which showed the minimum step angle is below 0.20″ under different torques. The positioning process included two modes: continuous mode and step mode. In continuous mode, the speed of the motor was controlled by PID control based on the tests of frequency-speed characteristic of the motor. In step mode, the step characteristics of the motor was tested under different load torques and applied different lengths of driving voltage to find the minimum of step angle. From the tests, the step angle increases rapidly with the periods of driving voltage and the single-step angle fluctuations of the motor with flexible shaft is much less than that of motor with normal shaft. Finally, the positioning performances of USM were tested. The results showed that the minimum positioning error of the motor with flexible shaft could achieve 0.37″ (1.79 μrad) and the time costed was below 1 s. • A flexible shaft was used to improve positioning precision of the ultrasonic motor. • Step performance of the USM was utilized to a certain limit, which was below 1.0″. • The minimum positioning error of the USM with flexible shaft could achieve 0.37″. • Positioning accuracy of the USM can reach sub-arc seconds under different torques. [ABSTRACT FROM AUTHOR]

The effective identification of the load torque is one of the key methods to improve the positioning accuracy of the position servo system, and the sliding mode observer (SMO) is a common identification method in the speed control system because of its advantages of insensitive parameters and easy physical realisation. However, the existing SMO cannot achieve high precision and high response identification of load torque in the full speed range when the motor is running at variable-speed or variable-load, which limits its application in the position servo system. Based on the analysis of the stability and the adaptive law of feedback gain coefficient, an improved SMO for adaptive identification based on adaptive control and improvement of cut-off frequency is proposed. To verify the proposed method, the dedicated simulation model and test platform are built. The results show that the proposed observer can realize the adaptive identification of the load torque under the condition of variable-speed or variable-load, and the estimation accuracy is high. The position servo system designed by the proposed observer can improve the response against load change, which is an effective method for high-precision positioning control of the position servo system with a variable-speed or variable-load. [ABSTRACT FROM AUTHOR]

In order to meet the needs of high precision, high availability and high safety positioning for automatic driving, aiming at the technical difficulties of automatic driving positioning in the complex urban environment, an inertial navigation model suitable for the dynamic characteristics of vehicles is established, and a tight combination method of Beidou / inertial high precision positioning is proposed, which solves the problem of rapid accumulation of positioning errors in the weak signal environment of Beidou. The results show that when the Beidou signal is completely interrupted and the INS is combined tightly, the positioning accuracy and continuity are improved significantly, and the maximum error is less than 0.5m, which can realize the automatic driving high-precision continuous navigation and positioning in the complex urban environment.

Aiming at the problem of high-precision location service of intelligent vehicle in the situation of weak or unavailable GPS signal( such as tunnel, underground parking lot, etc. ), this paper analyzed a kind of wireless positioning algorithm based on VANET, which used the information exchange between vehicles and intelligent subgrades to solve the problems of low effective accuracy and poor anti-interference ability in the existing vehicle positioning process. However, considering the dynamic changes of the network topology caused by vehicle movement, the existing researches often ignored the asymmetric communication delay between vehicles and intelligent subgrades, which led to the over-simplification of the cooperative positioning model and the loss of vehicle positioning accuracy. By describing the asymmetric communication model between vehicle and intelligent roadbed, it analyzed and verified the divergence of the existing vehicle cooperative positioning algorithm from a mathematical perspective. The simulation results show that the positioning error of the vehicle converges gradually without considering the asymmetric communication delay, but it shows exponential oscillation divergence with considering the asymmetric delay. [ABSTRACT FROM AUTHOR]

The high-precision positioning of GPS requires to detect and correct the cycle-slips in carrier phase more accurately and efficiently. In order to improve the ability of GPS single-frequency receivers to detect and correct small cycle-slips, the reason for the occurrence of cycle-slips and the principle of their detection and correction are analysed; then, a method of GPS single-frequency receivers' cycle-slip detection and correction based on wavelet transformation and LS-SVM is proposed. Here, WT is used to locate the cycle-slip and the LS-SVM is used to determine the value of it and correct it. The simulation results show that this method can detect and correct up to one cycle-slip accurately but in contrast, the traditional polynomial fitting method can only detect and correct at least two cycle-slips in the same condition. The feasibility of this method and its ability to accurately correct small cycle-slips are demonstrated.

The high-precision positioning of GPS requires to detect and correct the cycle-slips in carrier phase more accurately and efficiently. In order to improve the ability of GPS single-frequency receivers to detect and correct small cycle-slips, the reason for the occurrence of cycle-slips and the principle of their detection and correction are analysed; then, a method of GPS single-frequency receivers' cycle-slip detection and correction based on wavelet transformation and LS-SVM is proposed. Here, WT is used to locate the cycle-slip and the LS-SVM is used to determine the value of it and correct it. The simulation results show that this method can detect and correct up to one cycle-slip accurately but in contrast, the traditional polynomial fitting method can only detect and correct at least two cycle-slips in the same condition. The feasibility of this method and its ability to accurately correct small cycle-slips are demonstrated. [ABSTRACT FROM AUTHOR]

This study addresses the problem of robust fast and high‐precision positioning of uncertain one‐degree‐of‐freedom mechanical systems with friction and actuator constraint. The proposed control is constructed within the framework of saturated proportional–derivative (PD) plus relay action. Global asymptotic positioning stability is proven by Lyapunov's direct method with Barbalat's lemma. The appealing features of the proposed control are that it is fairly easy to construct with simple intuitive structure and the absence of modelling parameter in the control law formulation, and thus it is ready to implement for practical applications. An additive feature is that the proposed control embeds the PD action within one saturation function and hence it omits the elaborating embedment of the control gains within the requested constraint. Another feature is that the proposed approach can be explicitly upper bounded a priori and thus, it has the ability to protect the actuator from saturation completely and to ensure global asymptotic stability featuring fast transient and high steady‐state positioning. Numerical simulations and real experimental results demonstrate the effectiveness and improved performance of the proposed approach. [ABSTRACT FROM AUTHOR]

This study addresses the problem of robust faster and high‐precision positioning of uncertain one‐degree‐of‐freedom mechanical systems with friction. A very simple relay non‐linear proportional–derivative (PD) controller is proposed. Global asymptotic positioning stability is proven by Lyapunov's direct method invoking Barbalat's lemma. The appealing features of the proposed control are that it is fairly easy to construct with simple intuitive structure and without reference to modelling parameter and the ability to ensure global asymptotic positioning stability featuring faster transient and higher steady‐state precision. Simulations and experiments demonstrate the effectiveness and improved performance of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper presents a controller design approach to compensate for the disturbances and achieve robust vibration suppression against variations in the resonant frequency in a piezo-driven stage system. Disturbances such as nonlinearities due to hysteresis and creep phenomena are inherent in piezoelectric actuators, resulting in a low control performance of positioning or low tracking accuracy. Although various types of modeling and model-based approaches have been proposed to compensate for the nonlinearities, these approaches have limitations such as substantial modeling complexity, time-consuming modeling process, and high computational cost required for their evaluation and implementation. Moreover, resonant vibration modes in the mechanism lead to residual vibrations in the positioning or may even destabilize the system. In particular, the vibrational dynamics tend to have a low stability margin in piezo-driven systems because of sharp resonant peaks associated with the low structural damping. In this study, a state observer is employed to estimate the disturbance and vibration mode signals, wherein the observer is designed to suppress the disturbance and the vibration by using the estimated signals. Considering the hysterisis as an input disturbance to the linear plant renders complex modeling processes unnecessary. To compensate for the mechanical vibrations, pole-assignment method is used to achieve the gain-peak reductions and robustness against variations in the resonant frequency. The effectiveness of the proposed approach was verified by conducting experiments on a piezo-driven stage system.

Compliant mechanisms are nowadays a well-established means of achieving ultra-high precision, albeit at the expense of complex kinematics with the presence of parasitic motions. Diverse design configurations of compliant rotational joints called cross-spring pivots are hence studied in this work by applying various analytical and numerical approaches. Depending on the required precision and loading conditions, the limits of applicability of the available analysis tools, validated with nonlinear finite element calculations tuned with experimental data reported in literature, are established. The variation of design parameters allows, in turn, establishing design configurations of the studied mechanism that allow attaining minimized parasitic shifts and slight variations of its rotational stiffness, even when a broad range of rotations and varying transversal loads are considered, creating thus the preconditions for their application in high-precision micropositioning applications. [ABSTRACT FROM AUTHOR]

Compared with its counterparts, polarization sensitive optical time-domain reflectometry (P-OTDR) has two typical problems in terms of multi-point disturbance detection and high precision positioning, which restrict its practical applications. In this paper, we propose a novel method by using two-dimensional (2-D) image processing and statistical clustering. In place of the traditional spatial or temporal signal analysis way, the idea employs the temporally and the spatially uneven/inconsistent evolving patterns induced by the multiple individual events, and the proposed method is carried out to accumulate the temporally differentiated OTDR traces and then build up a 2-D temporal-spatial evolving graph, by using edge detection and automatic clustering to distinguish different disturbing points with precise locations. Through series of multi-point disturbance tests, the proposed method has been proved to have better performance than the conventional direct differentiation method and the fast Fourier transform spectrum analysis. [ABSTRACT FROM PUBLISHER]

The multi-antenna synchronized global navigation satellite system receiver is a high precision, low cost, and widely used emerging receiver. Using this type of receiver, the satellite and receiver clock errors can be eliminated simultaneously by forming between antenna single-differences, which is equivalent to the conventional double-difference model. However, current multi-antenna synchronized global navigation satellite system receiver products have not fully realized their potential to achieve better accuracy, efficiency, and broader applications. This paper introduces the conceptual design and derivable products of multi-antenna synchronized global navigation satellite system receivers involving the aspects of attitude determination, multipath effect mitigation, phase center variation correction, and ground-based carrier phase windup calibration. Through case studies, the advantages of multi-antenna synchronized global navigation satellite system receivers in high-precision positioning applications are demonstrated. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite Systems (GNSS) Carrier Phase (CP)-based high-precision positioning techniques have been widely used in geodesy, attitude determination, engineering survey and agricultural applications. With the modernisation of GNSS, multi-constellation and multi-frequency data processing is one of the foci of current GNSS research. The GNSS development authorities have better designs for the new signals, which are aimed for fast acquisition for civil users, less susceptible to interference and multipath, and having lower measurement noise. However, how good are the new signals in practice? The aim of this paper is to provide an early assessment of the newly available signals as well as assessment of the other currently available signals. The signal quality of the multi-GNSS (GPS, GLONASS, Galileo, BDS and QZSS) is assessed by looking at their zero-baseline Double Difference (DD) CP residuals. The impacts of multi-GNSS multi-frequency signals on single-epoch positioning are investigated in terms of accuracy, precision and fixed solution availability with known short baselines. [ABSTRACT FROM AUTHOR]

• Attitude error and velocity scale factor correcting based pipeline robot positioning method. • Optimization pipeline robot positioning technique of round-trip positioning data based on adaptive weights. • Pipeline mapping technique for underground pipeline robot based on inertial sensor/wheel odometer. For traditional underground pipeline robot based on the inertial sensor/wheel odometer, the outliers of the data collected by the positioning system, the attitude error of the inertial sensor and the velocity measurement error of the wheel odometer are crucial factors affecting positioning accuracy of the pipeline robot, and have a significant influence on underground pipeline maintenance and pipeline mapping. To solve the above three error factors, an enhanced positioning method for the underground pipeline robot based on the inertial sensor / wheel odometer is proposed in this paper. Firstly, basic principles including robot attitude calculation based on inertial sensors, robot velocity calculation based on wheel odometer, position calculation of pipeline robot and outliers elimination based on extrapolation fitting method are introduced; secondly, the velocity information and attitude angle of the pipeline robot is corrected by prior-backtracking method; thirdly, the round-trip positioning data optimization method based on adaptive weight is designed to improve the accuracy of the whole pipeline robot positioning system; finally, three pipelines with different lengths are introduced to verify the effectiveness and reliability of the proposed method. The experimental results show that the error of position information is no more than 0.18%, 0.07% and 0.11% of survey length, respectively. [ABSTRACT FROM AUTHOR]

• We propose a visual positioning method by leveraging the fiducial markers and factor graph to achieve reliable performance. • The method combines five factors (prior factor, range factor, projection factor, between factor, and IMU factor) for maximum a posteriori estimation and incremental optimization of the state of the robot in real time. • The positioning accuracy and robustness of the proposed method are verified under various operating conditions. High-precision positioning of agricultural robots is the key to the automation of greenhouse agricultural production. We propose a visual positioning method by leveraging the fiducial markers and factor graph to achieve reliable performance. This method consists of two parts, a front-end module and a back-end module. First, fiducial markers are involved to the front-end module to tackle the problems of unstructured and insufficient features in the greenhouse environment. A tag detection algorithm AprilTag2 is used to identify markers and extract feature points for the positioning purpose. Second, to eliminate the adverse effects of camera motion, mechanical vibration, and environmental disturbance on the positioning accuracy, the back-end module considers the characteristics of robot motion and the constraint relationship of variables, and correspondingly designs a positioning model based on the factor graph. The model combines five factors for maximum a posteriori estimation and incremental optimization of the state of the robot in real time. Finally, the positioning experiment of the wheeled robot was carried out at the motion speed of 0.26 m/s, 0.39 m/s, and 0.52 m/s. The experimental results show that the average errors of positioning are 0.056 m, 0.065 m, and 0.081 m, respectively, and the standard deviations of the errors are lower than 0.05 m. The visual positioning method based on fiducial markers and factor graph outperforms the mainstream positioning techniques in terms of positioning accuracy and robustness, and meet the high-precision positioning requirements in complex agricultural fields. [ABSTRACT FROM AUTHOR]

The first results of the short baseline single-epoch kinematic positioning based on dual-frequency real BeiDou/GPS data are presented. The performance of the BeiDou/GPS single-epoch positioning is demonstrated in both static and kinematic modes and compared with corresponding GPS-only performance. It is shown that the availability and reliability of the single-frequency BeiDou/GPS and dual-frequency BeiDou single-epoch kinematic positioning are comparable to those of the dual-frequency GPS. The fixed rate and reliability of ambiguity resolution for the single- and dual-frequency BeiDou/GPS are remarkably improved as compared to that of GPS-only, especially in case of high cutoff elevations. For positioning accuracy with fixed ambiguities, the BeiDou/GPS single-epoch solutions are improved by 23 and 4 % relative to the GPS-only case for two short baseline tests of 8 km, respectively. These results reveal that dual-frequency BeiDou real-time kinematic (RTK) is already applicable in Asia-Pacific areas and that single-frequency BeiDou/GPS RTK is also achievable but only with initialization of several seconds. More promisingly, the dual-frequency BeiDou/GPS RTK can overcome the difficulties with GPS-only RTK under the challenging conditions assuming, of course, that the additional BeiDou satellites are visible. [ABSTRACT FROM AUTHOR]

For indoor WLAN positioning it is difficult to achieve decimeter or centimeter-level precision questions, to IEEE1588v2 (PTP) precision network clock synchronization technology and the arrival time difference principle (TDOA), combined with non line of sight (NLOS) error mitigation techniques ranging research and design a set based on the existing WLAN (IEEE802.11x series of standards) device with high precision realtime location solutions. First, build a high-performance software-defined radio network communications platform, for accurate measurement of the radio signal arrival time and is calculated based on TDOA location. Secondly, the use of high-precision clock IEEE1588v2 standard equipment PTPGrand-2100 as a network clock source, through the integrated application of multi-hop latency compensation and asymmetric compensation algorithm to ensure nanosecond clock synchronization between the various WLAN access points (AP) accuracy(Experiments show that 1 nanosecond time synchronization error is equivalent to 10 to 30 cm of positioning error). Finally, based NLOS error becomes stability principle, filtered NLOS error and pre-positioned before the data, eliminate the influence of the greatest degree of NLOS error, the time domain error control in wireless ranging 5ns or less to achieve decimeter or more accurately estimate the position. The case can be widely used in mobile Internet, logistics management, mineral exploration, health and other needs of the precise location services (LBS) in other industry sectors.