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Despite the swift advancement of geometric calibration techniques, the geometric performance of remote sensing imagery remains heavily contingent upon the quality and distribution of ground control data. Securing precise ground control data is often laborious, and the accuracy of open-source control data is subject to variability. This paper explores the potential of the globally dispersed International GNSS Service (IGS) network to enhance the geometric performance of remote sensing images. The IGS network, with its extensive reach, offers superior positioning and navigation products that surpass the previously mentioned sources. To establish a connection between the IGS network and remote sensing images, high-resolution GEM chips (GEMs) are firstly utilized for precise positioning. Geolocation biases of these GEMs are refined based on the identified IGS information. After that, the calibrated GEM chips are applied as control information for the geometric calibration of raw satellite images. A test dataset from the Chinese Gaofen-2 (GF-2) with various forms of coverage is experimented, with LiDAR-derived Digital Surface Models (DSMs) serving as reference for the validation of the proposed method. Compared with traditional methods using the GEMs as a direct reference, the experimental results demonstrate that the introduced IGS information enhances the geometric performance of remote sensing images, exhibiting robust generalization performance across remote sensing data from various source domains. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology 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.)

Copyright of Urban Mass Transit is the property of Urban Mass Transit 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.)

Objective At present, CBTC (communication based train control) precise train positioning technology is prone to high cost of engineering construction and reconstruction, positioning errors and etc. Therefore, it is necessary to upgrade the existing train positioning method. Method The current commonly used technologies for train positioning are described. Based on the feature that the train is equipped with radar protection devices under TACS (train autonomous control system), a train mileage algorithm based on radar speed measuring integral is proposed. The principle of train autonomous positioning based on mileage mark is introduced. On this basis, a train real-time positioning function based on "speed measuring radar and electronic map" under TACS is put forward, and a real-time positioning method with radar speed measuring matching the electronic map is established. The above system is verified by the simulation platform. Result & Conclusion Simulation tests verify the effectiveness of the train real-time positioning function based on "speed measuring radar and electronic map" under TACS.

This paper introduces the current situation of intelligent development of shearer at home and abroad. The shearer is currently developing towards intelligent robotics and is in the primary stage of intelligence. This paper elaborates on the development process and trends of intelligent shearer. There are six scientific research projects that have played important roles in the intelligent development of shearer, including the UK remotely operated longwall face (ROLF) program, mine operating system (MINOS), NASA long wall automation cooperation project, Australian Australian coal industry’s research program (ACARP), Australian commonwealth scientific and industrial research organization (CSIRO) project, and EU new mechanisation and automation of longwall and drivage equipment (NEMAEQ). The development trend of shearer is to use continuously developing monitoring, sensing, and remote control technologies to replace manual intervention and operation, continuously improve the production efficiency and reliability of working face equipment, and develop towards informationization, integration, unmanned, and intelligent direction. This paper introduces the key technologies of intelligent perception, intelligent control, and intelligent communication of shearer. It points out that intelligent cutting technology based on coal rock recognition, intelligent drum speed regulation technology, precise positioning technology of shearer, and planning and mining technology based on three-dimensional geological models are key technologies that urgently need to be broken through. The human-machine relationship that cannot be ignored in the intelligent development process of shearer is discussed from two aspects: dust reduction and noise reduction.

The precise evaluation of micro-crack sizes and locations is crucial for the safe operation of structures. Traditional detection techniques, however, suffer from low spatial resolution, making it difficult to accurately locate micrometer-scale cracks. A method and experimental study were proposed in this paper for identifying and locating micro-cracks using optical fiber strain sensing based on OFDR to address this issue. The feasibility of this method for micro-crack detection was verified by the combination of a polyimide-coated sensing optical fiber (PISOF) and tight sheath sensing optical fiber (TSSOF). A calculation method for micro-crack widths based on distributed optical fiber strain curves was established, and the test results of different optical fibers were compared. Through multiple verification experiments, it was found that the strain peak curves of both fiber types could accurately locate micro-cracks with a precision of 1 mm. Additionally, the crack widths could be obtained by processing the distributed strain curves using a computational model, enabling the accurate capture of micro-crack characteristics at the 10 μm level. A strong linear relationship was observed between the optical fiber stretching length and the crack width. Notably, the relative error in calculating the crack width from the strain curve of PI fiber was very small, while a linear relationship existed between the maximum strain value of the TSSOF and the crack width, allowing for the calculation of the crack width based on the maximum strain value. This further validated the feasibility of the method designed in this paper for the analysis of micro-crack characteristic parameters. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department 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.)

In order to solve the problem that most of the existing mine-used smart phones only have the functions of voice calls, video photos, data transmission and so on, and do not have the functions of precise positioning, position coordinate display, message linkage, an identification card based on UWB technology is designed. The identification card realizes two-way data communication with the smart phone through low-power bluetooth. The identification card completes the precise positioning with the UWB station using the TOF positioning algorithm, obtains the position coordinate information, sends it to the smart phone through the low-power bluetooth (BLE), and displays the current specific position coordinates through the mine GIS roadway map on the smart phone APP. This paper introduces the key technologies of the identification card in detail, including mine roadway position coordinate model, precise positioning algorithm, message linkage reliable transmission mechanism, low power consumption sleep technology. The test results show that the positioning accuracy of the identification card is less than ± 0.3 meters, the positioning distance can reach 400 meters, the message linkage transmission delay is less than 2 seconds, the position coordinate display is accurate, the sleep current of the positioning module is less than 25 uA, and the average current meets the low power consumption design requirements.

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) 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.)

Copyright of Railway Construction Technology is the property of Railway Construction Technology 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.)

This article is devoted to the positioning of glued parts by robots in the process of manufacturing automotive headlights, with the possibility of generalization to the mutual positioning of any 3D object. The authors focused on the description of the mathematical method that leads to the optimization of the robot arm setting and ensures the closest contact of the glued parts. The contact surfaces of the two joined parts are, in the ideal case, identical in shape and their optimal alignment is considered to best align the position of the nominal points on the base part with the position of the control (measured) points on the part manipulated by the robot.

Despite the swift advancement of geometric calibration techniques, the geometric performance of remote sensing imagery remains heavily contingent upon the quality and distribution of ground control data. Securing precise ground control data is often laborious, and the accuracy of open-source control data is subject to variability. This paper explores the potential of the globally dispersed International GNSS Service (IGS) network to enhance the geometric performance of remote sensing images. The IGS network, with its extensive reach, offers superior positioning and navigation products that surpass the previously mentioned sources. To establish a connection between the IGS network and remote sensing images, high-resolution GEM chips (GEMs) are firstly utilized for precise positioning. Geolocation biases of these GEMs are refined based on the identified IGS information. After that, the calibrated GEM chips are applied as control information for the geometric calibration of raw satellite images. A test dataset from the Chinese Gaofen-2 (GF-2) with various forms of coverage is experimented, with LiDAR-derived Digital Surface Models (DSMs) serving as reference for the validation of the proposed method. Compared with traditional methods using the GEMs as a direct reference, the experimental results demonstrate that the introduced IGS information enhances the geometric performance of remote sensing images, exhibiting robust generalization performance across remote sensing data from various source domains.

A vision-based guidance methodology is proposed for precise positioning of the tool center point (TCP) of heavy-duty, long-reach (HDLR) manipulators. HDLR manipulators are non-rigid structures with many nonlinearities. Therefore, conventional rigid-body–based modeling and control methods issue challenges for accurate TCP positioning. To compensate for these errors, we compute the pose error between the TCP and an object of interest (OOI) directly in the camera frame, while using motion-based local calibration to find the extrinsic sensor-to-robot correspondence. The proposed pipeline for local calibration is twofold: first, the detected tool is oriented perpendicularly with respect to the OOI. Second, range adjustment is performed in the local planar plane by exploiting the visual measurements. Two methods for adjusting the range were examined: a line equation–based method and a trajectory matching–based method. Real-time experiments were conducted using a HDLR manipulator with a 5 m reach, and visual fiducial markers were used as detectable objects for the visual sensor. The experimental results demonstrated that the proposed methodology can provide sub-centimeter positioning accuracy, which is very challenging to achieve with HDLR manipulators due to their characteristic uncertainties. [ABSTRACT FROM AUTHOR]

To achieve a wide operating velocity range, stepping without backward motion, and high positioning resolution, a walking-type piezoelectric actuator with compliant mechanisms is developed. There are few academic research reports on this type of actuator, and this paper clarifies the features and advantages of this actuator. A systematic modeling and experimental evaluation of the proposed actuator are carried out. First, the configuration of the proposed actuator and the working principle of the alternating elliptical movements of the two driving feet are described. Then, dynamic models are built to simulate the output characteristics of the proposed actuator with in-phase and opposite-phase drive, which provide guidance for the design and optimization of walking-type actuators. An actuator prototype is fabricated and experimentally evaluated. The experimental results indicate that, under the opposite-phase drive, the proposed actuator can operate at a driving frequency of 1–15000 Hz. At a frequency of 14000 Hz, a maximum velocity of 24.6 mm/s is achieved at a voltage of 36 V pp , and the dead zone of the actuator is 0–6 V pp. A step displacement of 2.25 μm without backward motion is accomplished at a voltage of 72 V pp and a frequency of 1 Hz. Furthermore, the positioning resolution in the forward and reverse directions are 144 and 152 nm, respectively. The repeatability of the actuator is ±25 to ±50 nm for strokes of 325–725 nm, respectively. Therefore, compared to two driving feet being driven in phase, driving them in opposite phase as if they were walking has been confirmed to increase thrust, shorten the rise time, reduce the dead zone of driving voltage, eliminate backward motion, and provide high repeatability. • A piezoelectric actuator with triangular compliant mechanisms is first developed. • Dynamic models in the x - and y -directions are established for performance evaluation. • The actuator achieves a wide operating velocity range, no backward motion, and high-precision positioning. [ABSTRACT FROM AUTHOR]

Objective To investigate the effect of induced defecation technique with deep colonic precision localization in patients with complex constipation. Methods Fifty-three patients with complex constipation who were admitted to and consulted by the Department of Rehabilitation Medicine Center from November 2021 to May 2022 were recruited as research subjects. All patients received induced defecation with deep colonic precision positioning, and intervention effect was analyzed, Results The colonic deep-precision positioning induced defecation technique was reported to significantly relieve abdominal discomfort, bloating, constipation, diarrhea, and other intestinal disorders in 53 individuals with complex constipation. After the intervention, the patients had defecation in 49 (92. 45%)cases and no defecation in 4 (7. 55%)cases; 51 (96. 23%) cases and no defecation in 2 (3. 77%)case after the intervention; abdominal symptoms improved in a total of 53 (100. 00%)cases. The Wexner constipation score of the patients after the intervention was significantly lower than that before the intervention (P＜0. 05). Conclusion On patients with difficult constipation, the approach of induced defecation with deep colonic precision positioning provided considerable therapeutic benefits and significantly alleviated their clinical symptoms. (目的 探讨结肠精准定位的诱导排便技术在复杂性便秘患者中的应用效果。方法 对2021年11月—2022年5月江苏省人民医院康复医学中心收治及会诊的53例复杂性便秘患者进行结肠精准定位的诱导排便, 评估干预效果。结果 53例复杂性便秘患者在排除禁忌后接受结肠精准定位的诱导排便技术干预, 腹痛、腹胀、便秘、腹泻等肠道问题得到缓解。干预后患者排便49(92. 45%)例、未排便4(7. 55%)例; 干预后排气51(96. 23%)例、未排气2(3. 77%)例; 腹部症状改善共计53(100. 00%)例, 干预后患者Wexner便秘评分低于干预前, 差异有统计学意义(P＜0. 05)。结论 结肠精准定位的诱导排便技术对复杂性便秘患者有明显治疗效果, 能够有效减轻患者临床症状。)

The precise evaluation of micro-crack sizes and locations is crucial for the safe operation of structures. Traditional detection techniques, however, suffer from low spatial resolution, making it difficult to accurately locate micrometer-scale cracks. A method and experimental study were proposed in this paper for identifying and locating micro-cracks using optical fiber strain sensing based on OFDR to address this issue. The feasibility of this method for micro-crack detection was verified by the combination of a polyimide-coated sensing optical fiber (PISOF) and tight sheath sensing optical fiber (TSSOF). A calculation method for micro-crack widths based on distributed optical fiber strain curves was established, and the test results of different optical fibers were compared. Through multiple verification experiments, it was found that the strain peak curves of both fiber types could accurately locate micro-cracks with a precision of 1 mm. Additionally, the crack widths could be obtained by processing the distributed strain curves using a computational model, enabling the accurate capture of micro-crack characteristics at the 10 μm level. A strong linear relationship was observed between the optical fiber stretching length and the crack width. Notably, the relative error in calculating the crack width from the strain curve of PI fiber was very small, while a linear relationship existed between the maximum strain value of the TSSOF and the crack width, allowing for the calculation of the crack width based on the maximum strain value. This further validated the feasibility of the method designed in this paper for the analysis of micro-crack characteristic parameters.

A low-power multi-mode positioning information mining lamp is designed. By the fusion of multi-mode radio frequency technology and radio frequency scheduling method, the mine can realize the seamless transition and upgrading from regional positioning to ultra wideband accurate positioning; PA power amplifier and LNA low noise amplifier are used to optimize the transmission distance and ranging accuracy of UWB radio frequency technology, so as to solve the base station capacity and economic cost of underground location service system; at the same time, the upgradable design can realize the differentiated customized use needs, and can better provide underground location information services for coal mines.

The advantages and disadvantages of five commonly used mining monorail cranes, namely explosion-proof diesel engine monorail crane, explosion-proof battery monorail crane, pneumatic monorail crane, rope traction monorail crane, and cable dragging monorail crane, are analyzed. It is pointed out that explosion-proof diesel engine monorail crane and explosion-proof battery monorail crane have been widely used for underground equipment and material transportation in coal mines due to their strong transportation capacity. The explosion-proof battery monorail crane has green and clean features. It has gradually become a key research and development equipment for underground auxiliary transportation in coal mines. This paper analyzes the research status of the mining monorail crane system from four aspects of battery drive, positioning, measurement and control, and information transmission. It is pointed out that the current mining monorail crane system has low automation and intelligence levels. To achieve intelligent transportation of the monorail crane, it is necessary to study the key technologies such as lithium battery explosion-proof and battery management of the monorail crane, global and local fusion precise positioning, multi-sensor information fusion intelligent measurement and control, edge computing information transmission, etc. For the explosion-proof and battery management technology of lithium battery, a topology optimization design method of explosion-proof large capacity lithium battery structure based on variable density method, and a balanced management scheme based on improved sparrow search algorithm/genetic algorithm are proposed. For precise positioning technology, a global positioning method based on inertial navigation and odometer fusion, and a local positioning method based on visual+UWB combination are proposed. For intelligent measurement and control technology, an intelligent detection method based on recursive least squares algorithm/second-order approximate extended Kalman filter , the real-time construction method for follow-up electronic fences, and vector control method based on fuzzy rules are proposed. For the information transmission technology, the 'local-short range-ground' communication system architecture based on the fusion of 5G network and the distributed data calculation and transmission method based on edge computing are proposed. The proposal of key technical issues and solutions for intelligent monorail cranes in coal mines provides a new approach to accelerate the development of intelligent monorail cranes in coal mines.

High-precision positioning from Global Navigation Satellite Systems (GNSS) has garnered increased interest due to growing demand in various applications, like autonomous car navigation and precision agriculture. Precise Point Positioning (PPP) offers a distinct advantage over differential techniques by enabling precise position determination of a GNSS rover receiver through the use of external corrections sourced from either the Internet or dedicated correction satellites. However, PPP's implementation has been challenging due to the need to mitigate numerous GNSS error sources, many of which are eliminated in differential techniques such as Real-Time Kinematics (RTK) or overlooked in Standard Point Positioning (SPP). This paper extensively reviews PPP's error sources, such as ionospheric delays, tropospheric delays, satellite orbit and clock errors, phase and code biases, and site displacement effects. Additionally, this article examines various PPP models and correction sources that can be employed to address these errors. A detailed discussion is provided on implementing the standard dual-frequency (DF)-PPP to achieve centimeter- or millimeter-level positioning accuracy. This paper includes experimental examples of PPP implementation results using static data from the International GNSS Service (IGS) station network and a kinematic road test based on the actual trajectory to showcase DF-PPP development for practical applications. By providing a fusion of theoretical insights with practical demonstrations, this comprehensive review offers readers a pragmatic perspective on the evolving field of Precise Point Positioning. [ABSTRACT FROM AUTHOR]

The object of research is the onboard subsystems of Unmanned Aerial Vehicles (UAVs). The research is aimed at analyzing UAVs, specifically the integration and enhancement of satellite-based positioning systems, including Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS). The problem concerns traditional satellite-based positioning services, especially those relying solely on medium earth orbit (MEO) satellites, which are insufficient for specific requirements. The study aims to address the limitations of these systems on onboard subsystems of UAVs, especially in challenging environments laden with jammers and interference, and to provide a more accurate, robust, and continuous positioning solution. The research proposes a «multilayer system of systems» approach that integrates signals from various sources, including low Earth orbit (LEO) satellites, ground-based positioning, navigation, and timing (PNT) systems, and user-centric sensors. The combined approach, termed LeGNSS/INS, leverages the strengths of each component, providing redundancy and enhanced accuracy. The system’s performance was evaluated using pseudo-real output data, demonstrating its ability to generate quasi-real dynamic trajectories for UAV flight. The error analysis showed that the proposed method consistently outperforms traditional GNSS systems, especially in challenging environments. The enhanced performance of the LeGNSS/INS system can be attributed to integrating multiple satellite systems with INS and applying optimal filtering techniques. The research also employed mathematical modeling to represent the dependencies and interactions when combining data from different sources, such as GPS, LEO, and INS. The Kalman filter is a mechanism to fuse data from multiple sources optimally. The insights from this study apply to various sectors, including aviation, maritime navigation, autonomous drones, and defense. The enhanced positioning accuracy can significantly improve safety, navigation precision, and operational efficiency. However, the study assumes idealized conditions for satellite signal reception, which might not always be accurate in real-world scenarios. Challenges, such as the martial law conditions in Ukraine affecting data collection and potential satellite signal restrictions, were also highlighted. Further research can delve into the impact of more complex environmental factors and the integration of additional satellite systems or sensors to enhance accuracy further. [ABSTRACT FROM AUTHOR]

Devices known as kinematic couplings offer accurate, repeatable, and stiff connections between two parts. They are characterized by point contacts and enable great repeatability with errors less than 1 micron, in contrast to conventional coupling systems like alignment pins or those based on elastic deformation. In this study, a robotized laser-cutting machine is equipped with a three-groove kinematic coupling design to increase the precision of workpiece placement. Given the application's requirements, a preliminary design of the coupling is defined. An analytical approach is provided for calculating stresses and deflections at the locations where balls and grooves make contact, and it is then utilized to calculate positioning errors caused by the mechanical structure's elastic deformation under various loading conditions. The outcomes of the simulations are finally discussed and highlight the efficacy of the solution tested. [ABSTRACT FROM AUTHOR]

Underground coal mines belong to the GNSS-denied environment, and the Strapdown Inertial Navigation System (SINS) has a significant advantage in the precise positioning of equipment in this environment because of its operation without requiring interaction with external information and strong anti-interference capabilities. Nonetheless, the vibrations of the installation platform adversely affect the positioning accuracy of SINS. This article focuses on the monorail crane in coal mines as the subject of research, developing a dynamic model for the motion unit consisting of the "track + drive unit + driver's cab", while analyzing the relationship between track roughness conditions and the vibration excitation of this unit. Subsequently, utilizing the dynamic model, the study calculated the angular and linear vibration characteristics and formulated models to address coning error and sculling error specific to the SINS in this vibration condition. Lastly, by employing a multi-sample compensation algorithm, this article compensated for positioning errors in the SINS caused by track roughness-induced vibrations during uniform straight-line motion of the motion unit, thus achieving optimal positioning information for the monorail crane. The simulation results demonstrated that employing a four-sample compensation algorithm reduces the coning error in SINS positioning calculations by a minimum of 50% and decreases the sculling error by at least 31%, satisfying the positioning accuracy requirements for precise parking of the monorail crane during the transportation phase, while establishing the foundation for autonomous precise positioning and integrated navigation of underground track transport equipment in coal mines. [ABSTRACT FROM AUTHOR]

We combine accelerometer and asynchronous high-rate GNSS data to retrieve dynamic displacements. The method adopts relative GNSS positioning with observations of different sampling rates at rover and reference stations. The objective is to examine the feasibility of downsampling GNSS data at reference stations and thus, verify whether permanent GNSS networks collecting low-rate observations can serve as reference sites. The performance is assessed using a shake table to induce displacement waveforms. We show that the combined GNSS and accelerometer solution improves displacement accuracy by half compared to the GNSS-only one. Further accuracy improvement is obtained by applying the Rauch Tung Striebel (RTS) smoother. Consequently, it is reasonable to downsample high-rate GNSS data at the reference station even to a 2 s interval and preserve the displacement error below 1 mm. The results also reveal that a fusion of GNSS with accelerometer and RTS smoothing helps to mitigate the ephemeris error. With the assessment in the time–frequency domain, we show that the combined solution better recovers displacement waveforms than GNSS-only. For the former solution, the detected peak frequencies agree very well with those of the Linear Variable Differential Transformer responsible for providing the ground truth displacements, and the amplitude error does not exceed 0.5 mm. We conclude that the proposed approach based on asynchronous GNSS observations provides millimeter-level precision results and is better for reconciling dynamic displacements than a GNSS-only solution or simply integrating accelerometer data. [ABSTRACT FROM AUTHOR]

With the rapid development of civil aviation industry, more and more tasks are required to fuel the aircraft. At present, the aircraft refueling task is mainly assigned to the refueling personnel by the dispatcher of the fuel supplier, one by one, according to the flight refueling information, after receiving the task, the refueling operator drives the refueling vehicle to the aircraft for refueling operation. The realization of electronic, information and big data analysis technology has gradually opened up the information channel of refueling system. Based on a large number of multi-dimensional data, according to the characteristics of aircraft refueling operation, an intelligent dispatching method for aircraft refueling vehicle is provided, which can automatically assign refueling tasks, avoid flight delays and the resulting serious waste of resources and can reduce the workload of the dispatcher. Through the intelligent dispatch, refueling resources can be reasonably allocated to ensure the timely refueling of aircraft and smooth completion of flight support tasks.

Today's technological developments make it possible to use machines to perform specific tasks instead of humans. However, the challenge for such autonomous devices is to precisely move and navigate in constantly changing external environments. In this paper, the influence of varying weather conditions (air temperature, humidity, wind speed, atmospheric pressure, type of satellite systems used/satellites visible, and solar activity) on the accuracy of position determination was analyzed. To reach the receiver, a satellite signal must travel a great distance and pass through all layers of the Earth's atmosphere, the variability of which causes errors and delays. Moreover, the weather conditions for receiving data from satellites are not always favorable. In order to investigate the impact of delays and errors on position determination, the measurements of the satellite signal were conducted, the motion trajectories were determined, and the standard deviations of these trajectories were compared. The results obtained show that it is possible to achieve high precision in determining the position, but varying conditions, such as solar flares or satellites' visibility, meant that not all measurements are able to achieve the required accuracy. The use of the absolute method of satellite signal measurements contributed to this to a large extent. To increase the accuracy of positioning by GNSS systems, it is first of all proposed to use a dual-frequency receiver that eliminates ionospheric refractions. [ABSTRACT FROM AUTHOR]

Aiming at the practical problem of the difficulty in identifying associated users when abnormal line loss occurs in the station area, a method for judging and accurately locating the line loss abnormality in the station area based on the correlation measurement algorithm is proposed. Firstly, the optimal clustering number of the data set is determined by the gap statistics-contour coefficient fusion algorithm, and on this basis, the dichotomous K-means++ is used to construct the station area line loss standard library. Secondly, the station area line loss anomaly identification is completed based on the standard library and then the abnormal time is determined. The Spearman correlation coefficient (SCC) and Euclidean-discrete Frand#233;chet distance (E-DFD) of each user's power and line loss during the abnormal time is calculated. And based on SCC and E-DFD, a comprehensive evaluation index to analyze user relevance is estabilished. Finally, the technique for order preference by similarity to an ideal solution (TOPSIS) is used to sort the comprehensive evaluation index values to achieve precise positioning of abnormally associated users. The calculation example uses real field data in a certain area to analyze, and the results show that the method proposed in this paper has better performance in clustering effectiveness, calculation time, and identification accuracy.

GNSS positioning in urban scenarios suffers for the scarce visibility of satellites. Integration with 5G services for positioning could improve this situation. In this paper, the digital surface models (DSMs) relevant to different urban scenarios, namely residential streets and urban canyons, are simulated around one observer in northern Italy (Milano) for one day of the year chosen as an example. The time series of the number of in-view GNSS satellites, their geometry and the derived quality indexes (position dilution of precision (PDOP)) are computed and analyzed. As expected, in urban canyons, a significant number of epochs does not provide four satellites within view, and many more epochs present really mediocre PDOPs. In residential streets, the situation is always quite fair. Different geometric configurations of 5G base stations are simulated around the observer. The availability of 5G times of arrival (ToAs) and their differences (TDoAs) is hypothesized, and the integration of these observations with GNSS pseudoranges is analyzed, again in terms of the PDOPs. In residential streets, 5G availability improves the positioning. In urban canyons, the optimal configuration of 5G base stations (five base stations around the observer) completely solves the positioning problem for all the epochs of the day. Less favorable configurations (four and three base stations) improve epochs with poor PDOPs in a GNSS-only configuration. They allow the positioning of epochs with few satellites but cannot completely replace the GNSS. [ABSTRACT FROM AUTHOR]

At present, most of the positioning methods of underground tunneling equipment in coal mines adopt single auxiliary measurement methods such as machine vision, odometer and total station to combine with inertial navigation measurement to suppress the cumulative position error caused by inertial navigation solution over time. However, the single auxiliary measurement method is easy to be affected by the underground environment, and there are certain errors in position measurement, which leads to the reduction of the precision of the combined measurement method with inertial navigation. In order to solve the above problems, taking shield roadheader robot system in coal mine as the research object, a combined positioning method of strapdown inertial navigation+digital total station+displacement sensor is proposed. Firstly, the position and attitude angle parameters of the roadheader robot are calculated by using strapdown inertial navigation. Secondly, the position information of the roadheader robot measured by the digital total station and calculated by the displacement sensor are used to feedback and correct the position information calculated by the strapdown inertial navigation, so as to reduce the cumulative position error generated by the inertial navigation over time. Finally, the position and attitude angle information calculated by the strapdown inertial navigation, the position information obtained by the total station measurement and the position information estimated by the displacement sensor are fused by the multi-information fusion algorithm based on the federated filter, so as to obtain the accurate position and attitude information of the roadheader robot. The simulation and industrial experiment results show that the combined positioning method can well suppress the accumulative position solution errors of pure inertial navigation and realize the precise positioning of the shield roadheader robot in coal mines. The position errors in the x-axis and y-axis directions are controlled at ±0.03 m and ±0.02 m respectively, which meets the requirements of the underground driving face.

High-precision positioning from Global Navigation Satellite Systems (GNSS) has garnered increased interest due to growing demand in various applications, like autonomous car navigation and precision agriculture. Precise Point Positioning (PPP) offers a distinct advantage over differential techniques by enabling precise position determination of a GNSS rover receiver through the use of external corrections sourced from either the Internet or dedicated correction satellites. However, PPP’s implementation has been challenging due to the need to mitigate numerous GNSS error sources, many of which are eliminated in differential techniques such as Real-Time Kinematics (RTK) or overlooked in Standard Point Positioning (SPP). This paper extensively reviews PPP’s error sources, such as ionospheric delays, tropospheric delays, satellite orbit and clock errors, phase and code biases, and site displacement effects. Additionally, this article examines various PPP models and correction sources that can be employed to address these errors. A detailed discussion is provided on implementing the standard dual-frequency (DF)-PPP to achieve centimeter- or millimeter-level positioning accuracy. This paper includes experimental examples of PPP implementation results using static data from the International GNSS Service (IGS) station network and a kinematic road test based on the actual trajectory to showcase DF-PPP development for practical applications. By providing a fusion of theoretical insights with practical demonstrations, this comprehensive review offers readers a pragmatic perspective on the evolving field of Precise Point Positioning.

Mobile laser scanning technology used for deformation detection of shield tunnel is usually two-dimensional, which is expanded into three-dimensional (3D) through mileage, resulting in low positioning accuracy. This study proposes a 3D laser point cloud positioning method that is divided into rings in the mileage direction and blocks in the ring direction to improve the positional accuracy for shield tunnels. First, the cylindrical tunnel wall is expanded into a plane and the bolt holes are extracted using the self-adaptive parameter adjustment cloth simulation filter (CSF) algorithm combined with a density-based spatial clustering of applications with noise (DBSCAN) algorithm. Second, the mean-shift algorithm is used to obtain the center point of the bolt hole, and a model is designed to recognize the center point of different splicing blocks. Finally, the center point is combined with the standard straight-line equation to fit the straight-line positioning seam, achieving an accurate ring and block segmentation of a shield tunnel as a 3D laser point cloud. The proposed method is compared with existing methods to verify its feasibility and high accuracy using the seams located by the measured tunnel point cloud data and in the measured point cloud. The average differences between the circumferential seams positioned using the proposed method and those in the point cloud at the left waist, vault, and right waist were 3, 4, and 5 mm, respectively, and the average difference between the longitudinal seams was 3.4 mm The proposed research method provides important technical and theoretical support for tunnel safety monitoring and detection. [ABSTRACT FROM AUTHOR]

To complete the wiring operation of the main transmission line stripped of its insulating skin in a live power distribution system, a structured-light binocular vision method is utilized to identify and locate the line. First, aiming at the interference of the background information, a depth threshold segmentation method is used to filter the background area. Second, a mean filtering method is proposed to filter out the mismatch noise of a binocular vision camera in an outdoor environment. The Canny algorithm is then utilized to extract the contour, the central axis of the main transmission line is fitted, and the difference in the neighborhood pixel value is used to recognize the stripping area. Finally, the spatial equation and attitude of the central axis of the fitting transmission line are obtained along with the central coordinates of the stripping area, guiding the robot to carry out the wiring. [ABSTRACT FROM AUTHOR]

Piezoelectric stick-slip actuators (PSSAs) are famous for ultimate working condition adaptability, simple structure, and positioning accuracy. To meet the demand of industrial application, lots of PSSAs designed with flexure hinge mechanisms (FHMs-PSSAs) have been developed to realize the requirements of translational motion, rotational motion, multidegree-of-freedom (multi-DOF) motion. The output performance of the FHMs-PSSAs has been greatly improved, including load capacity, speed, and accuracy; moreover, some approaches to solve the problem of the backward motion are provided as well. In this work, the working principle of FHMs-PSSAs is introduced, and the excitation signals applicable to FHMs-PSSAs are summarized. Based on the current research and development status, the progress of structure design of FHMs-PSSAs is introduced in accordance with translatory FHMs-PSSAs, rotary FHMs-PSSAs, and multi-DOF FHMs-PSSAs. Additionally, the developed analysis methods and design schemes to improve the performance are introduced, including theoretical analysis methods, consistency scheme of forward and reverse performance, suppression scheme of the backward motion, and improvement scheme of positioning accuracy. The significance of this work can be regarded as a further supplement to the previous review articles on the PSSAs, which will provide a reference and guidance for the future development of FHMs-PSSAs. [ABSTRACT FROM AUTHOR]

This paper proposes an implementation scheme of wireless upgrade firmware program based on UWB and ZigBee technologies. This method adopts one-to-many networking mode and infinite loop multi-broadcast mechanism to realize the location card batch wireless upgrade, which improves the speed, concurrent capacity and efficiency of wireless upgrade. The test results show that the concurrent number of locating card in batch upgrade is not limited. Within the coverage area of 100 meters, 95% locating cards are successfully upgraded once, 5% locating cards need to wait for two cycles, and the wireless upgrade time is less than 5 minutes. Therefore, this method provides a fast, reliable and convenient wireless upgrade way for a large number of locating card upgrade firmware programs.

Underground coal mines belong to the GNSS-denied environment, and the Strapdown Inertial Navigation System (SINS) has a significant advantage in the precise positioning of equipment in this environment because of its operation without requiring interaction with external information and strong anti-interference capabilities. Nonetheless, the vibrations of the installation platform adversely affect the positioning accuracy of SINS. This article focuses on the monorail crane in coal mines as the subject of research, developing a dynamic model for the motion unit consisting of the “track + drive unit + driver’s cab”, while analyzing the relationship between track roughness conditions and the vibration excitation of this unit. Subsequently, utilizing the dynamic model, the study calculated the angular and linear vibration characteristics and formulated models to address coning error and sculling error specific to the SINS in this vibration condition. Lastly, by employing a multi-sample compensation algorithm, this article compensated for positioning errors in the SINS caused by track roughness-induced vibrations during uniform straight-line motion of the motion unit, thus achieving optimal positioning information for the monorail crane. The simulation results demonstrated that employing a four-sample compensation algorithm reduces the coning error in SINS positioning calculations by a minimum of 50% and decreases the sculling error by at least 31%, satisfying the positioning accuracy requirements for precise parking of the monorail crane during the transportation phase, while establishing the foundation for autonomous precise positioning and integrated navigation of underground track transport equipment in coal mines.

This paper analyses the regularization of an ill-conditioned mathematical model in a single-epoch precise GNSS positioning. The regularization parameter (RP) is selected as a parameter that minimizes the criterion of the Mean Squared Error (MSE) function. The crucial for RP estimation is to ensure stable initial least-squares (LS) estimates to replace the unknown quadratic matrix of actual values with the LS covariance matrix. For this purpose, two different data models are proposed, and two research scenarios are formed. Two regularized LS estimations are tested against the non-regularized LS approach. The first one is the classic regularization of LS estimation. In turn, the second one is its iterative counterpart. For the LS estimator of iterative regularization, regularized bias is significantly lower while the overall accuracy is improved in the sense of MSE. The regularized variance-covariance matrix of better precision can mitigate the impact of regularized bias on integer least-squares (ILS) estimation up to some extent. Therefore, iterative LS regularization is well-designed for single-epoch integer ambiguity resolution (AR). Nevertheless, the performance of the ILS estimator is studied in the context of the probability of correct integer AR in the presence of regularized bias. [ABSTRACT FROM AUTHOR]

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Benefitting from the multifunctional properties of knitted fabrics with elasticity, flexibility, and high resilience, knitted strain sensors based on structure and strain performance are widely utilized in sports health due to their adaptability to human movements. However, the fabrication process of common strain sensors mainly relies on experienced technicians to determine the best sensor size through repeated experiments, resulting in significant size errors and a long development cycle. Herein, knitted strain sensors based on plain knit were fabricated with nylon/spandex composite yarn and silver-plated nylon yarn using a flat knitting process. A size prediction model of knitted strain sensors was established by exploring the linear relationship between the conductive area size of samples and knitting parameters via SPSS regression analysis. Combined with stable structures and high performance of good sensitivity, stability, and durability, the knitted strain sensors based on size prediction models can be worn on human skin or garments to monitor different movements, such as pronunciation and joint bending. This research indicated that the reasonable size control of the knitted strain sensor could realize its precise positioning in intelligent garments, exhibiting promising potential in intelligent wearable electronics. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the underground positioning of coal mine mostly depends on RFID positioning technology, and the upgrade cost of accurate positioning is high, a multi-positioning technology protocol fusion positioning system is proposed. While compatible with regional positioning, the system can realize the access of ZigBee technology and UWB technology positioning equipment, reduce the cost of precise positioning upgrade, realize the upgrading of coal mine personnel positioning technology, promote the fusion development of RFID regional positioning and ZigBee and UWB precise positioning technology, further improve the positioning accuracy of underground positioning system, and build a highly reliable and full coverage information system interactive network, this paper proposes a positioning system which can realize three positioning methods for data interaction, to meet the application requirements of different areas and different application scenarios.

The positioning accuracy of the precise personnel positioning system in underground mine is affected by the non-line-of-sight error and clock error. At present, the system mostly uses Kalman filter-based positioning method to reduce the error, but the positioning accuracy is not high when there is gross error in the measured data. In order to solve this problem, a precise personnel positioning method in underground mine based on grey prediction model is proposed. When a person carrying a marker card enters the coverage area of the positioning reader, the positioning reader calculates the measured distance between the marker card and the reader through wireless positioning technology and stores the measured distance into the data cache area. According to the measured distance in the data cache area, the GM (1, 1) model is used to calculate the predicted distance between the marker card and the reader at the next moment. When the prediction accuracy level of this predicted distance is excellent and the difference with the measured distance exceeds the error judgment threshold, the predicted distance is used to replace the measured distance to achieve the optimal compensation of the distance measurement error. The test results show that the method is not affected by the distance measurement error. When there is a gross error in the measured distance, the positioning accuracy of this method is significantly better than that of the Kalman filter-based positioning method.

Thalamic hemorrhage is one of deep-seating cerebral lesions. Conservative therapy is preferred to patients with minor thalamic hemorrhage, and external ventricular drainage is usually applied in patients with cerebral ventricular hemorrhage. However, the prognosis of some patients is poor. This study intends to explore that minimally invasive puncture to remove hematoma in patients with the thalamic hemorrhage volume less than 15 ml with disturbance of consciousness (especially the expansion of the hematoma to the hypothalamus or midbrain) is an alternative method. In clinical practice, a wedge-shaped sign of thalamic hemorrhage could be observed in CT images in coronal plane, which was featured by the compression of hematoma on the third ventricle and the aqueduct of midbrain shaped like a wedge into the mesencephalon. The obstruction of cerebrospinal fluid circulation was then evaluated. For persistent hematoma oppression, the precise positioning of stereotactic instrument could be applied to rapidly and effectively remove the oppression, thus improving life quality of affected patients.