Accurate Positioning Research Articles

Improving the dynamic positioning accuracy of the electro-hydraulic drive

Research is focused on improving the dynamic accuracy of control surface positioning during the switching of hydraulic actuator modes and studying the processes and phenomena that cause control surface overshoot. Existing studies on the dynamic accuracy of hydraulic actuators have been analyzed. Transitional processes occurring in the " electromagnetic recirculation valve – electronic control unit" loop during changes in hydraulic actuator operating modes have been examined. The features of processes and physical phenomena leading to increased activation time of the hydraulic actuator have been identified. Solutions and electrical connection schemes for connecting the hydraulic actuator recirculation valve to the electronic control unit have been proposed to meet the accuracy positioning and activation time requirements. Experimental studies have been conducted to simulate the operational mode of hydraulic actuators, and failure situations modes under various load forces have been identified. Based on the results, principles for designing connection schemes for the electromagnetic recirculation valve of the hydraulic-mechanical actuator to the electronic control unit, which enhance system positioning accuracy at the structural level, have been formulated. Technical solutions aimed at achieving the specified accuracy and activation time for the hydraulic actuator have been developed and practically tested. The effectiveness and suitability of the proposed solutions for operational use, considering external factors, have been experimentally confirmed.

Isolated point clutter suppression method for airborne STAP radar in wind farm environment

With the large-scale construction of wind farms, wind turbine isolated point clutter has an increasingly serious impact on airborne radar target detection performance. Traditional space-time adaptive processing methods cannot suppress wind turbine clutter (WTC) with spectrum broadening characteristics, which may lead to a decrease in target detection probability and an increase in false alarm rate. In this paper, a WTC suppression method for airborne radar based on micro-Doppler features is proposed, and we construct the feature subspace of wind turbine echo to distinguish wind turbine, target, clutter, and noise. First, the Sobel operator is used to process the radar range-Doppler spectrum, and the range cells of the wind turbines are preliminarily judged. Then the smallest of constant false alarm rate (SOCFAR) method is used to further confirm the range cells where the wind turbines are located. Next, Mahalanobis distance is used to estimate the optimal dictionary atomic parameters of WTC, and the updated dictionary atoms are used to construct an orthogonal projection matrix to suppress WTC. Finally, short-range nonstationary clutter and sidelobe clutter are suppressed by space-time adaptive segment processing. On the one hand, the proposed method realizes the accurate positioning of wind turbines through image edge detection and constant false alarm detection. On the other hand, Mahalanobis distance is used to estimate the atomic parameters of the wind turbine dictionary, which ensures the homogeneity of wind turbine samples after clutter suppression. The simulation and measured data results show that the proposed method can significantly reduce the false alarm rate caused by WTC while ensuring the effective detection of the target.

Fluid-Infiltrated Metalens-Driven Reconfigurable Intelligent Surfaces for Optical Wireless Communications.

A reconfigurable intelligent surface (RIS), a leading-edge technology, represents a new paradigm for adaptive control of electromagnetic waves between a source and a user. While RIS technology has proven effective in manipulating radio frequency waves using passive elements such as diodes and MEMS, its application in the optical domain is challenging. The main difficulty lies in meeting key performance indicators, with the most critical being accurate and self-adjusting positioning. This work presents an alternative RIS design methodology driven by an all-silicon structure and fluid infiltration, to achieve real-time control of focal length toward a designated user, thereby enabling secure data transmission. To validate the concept, both numerical simulations and experimental investigations of the RIS design methodology are conducted to demonstrate the performance of fluid-infiltrated metalens-driven RIS for this application. When combined with different fluids, the resulting ultra-compact RIS exhibits exceptional varifocal abilities, ranging from 0.4 to 0.5 mm, thereby confirming the adaptive tuning capabilities of the design. This may significantly enhance the modulation of optical waves and promote the development of RIS-based applications in wireless communications and secure data-transmission integrated photonic devices.

Improving Indoor WiFi Localization by Using Machine Learning Techniques

Accurate and robust positioning has become increasingly essential for emerging applications and services. While GPS (global positioning system) is widely used for outdoor environments, indoor positioning remains a challenging task. This paper presents a novel architecture for indoor positioning, leveraging machine learning techniques and a divide-and-conquer strategy to achieve low error estimates. The proposed method achieves an MAE (mean absolute error) of approximately 1 m for latitude and longitude. Our approach provides a precise and practical solution for indoor positioning. Additionally, some insights on the best machine learning techniques for these tasks are also envisaged.

Design and simulation of electronic communication positioning system based on Internet of Things technology

As electronic information technology continuously develops, it has gradually been applied to various industries and plays a vital role in the Internet of Things (IoT). The electronic communication positioning system is an interrelated aggregate or component composed of combining electronic science and technology with information science and technology to determine the spatial position. The current electronic communication positioning system has low positioning accuracy in indoor environments and is easily affected by obstacles such as building structures and walls, making it difficult to achieve accurate positioning. This paper integrated the IoT technology into the design and simulation experiment of the electronic communication system, aiming to improve the stability and accuracy of the positioning system and improve the quality of the location information service in the current stage of the market. This paper first introduced the architecture of the IoT, including RFID technology analysis and ZigBee technology analysis. Then it studied the classification of common positioning algorithms, and finally conducted a simulation test on the electronic communication positioning system based on the IoT technology in the experimental part. Compared with the traditional electronic communication positioning system, the tested results show that the minimum error of the electronic communication positioning system based on the IoT technology can reach 0.102. The maximum time accuracy can reach 95.34%, proving its effectiveness. In practical application, its error and time accuracy can achieve the required level of location information service. This article provided a brief explanation of the application of electronic information technology in the IoT system to assist in the further development of the IoT.

Robust Model Predictive Control for an Ion Beam Shepherd in a large-debris removal mission

The increasing accumulation of space debris poses significant risks to spacecraft, making the development of effective debris mitigation technologies necessary. This paper explores the Ion Beam Shepherd (IBS) method as a potential contactless solution for deorbiting large debris objects. The IBS system concept involves a spacecraft equipped with an ion thruster to direct a controlled ion beam at the debris, generating a small force that gradually lowers its orbit. A proposed configuration of the chaser’s actuator system integrates radial and out-of-plane cold-gas thrusters along with in-track ion thrusters to enhance control and safety while maintaining low mission costs. A robust Model Predictive Control (MPC) strategy is implemented, using the theory of MPC for Tracking to ensure accurate positioning and effective deorbiting. This theoretical approach addresses uncertainties and perturbations to robustly guarantee safe distances between the chaser and the debris. Additionally, a new ray-marching-based algorithm is introduced to estimate the force and torque exerted by the ion beam on the target, considered as a 6 degrees of freedom object, improving simulation accuracy and control performance assessment. A comprehensive simulation of the deorbit of a large debris object is performed, demonstrating the potential of the IBS technology for future large-debris removal missions. This research advances the conceptual framework and control techniques for the IBS technology, advancing towards its future implementation in space debris mitigation.

Collaborative attitude stabilization and distributed vibration suppression of satellite with ultra–large flexible antenna

Large flexible radar satellites are widely used in space–based remote sensing for wide–area target observation and high–capacity information transmission. To achieve accurate earth observation and structural stability of an ultra–large flexible satellite in hundred–meter length concurrently, this paper presents two–time–scale collaboration for attitude stabilization and vibration suppression. First, the coupling dynamic model of the satellite with ultra–large flexible antenna is established under space disturbances. Next, singular perturbation with boundary layer correction is employed to decompose attitude and vibration controls in different time scales, respectively. Given the respective decoupling models, the slow subsystem employs an angles–only terminal sliding–mode controller with adaptive switching and input saturation to accomplish high–robustness triaxial attitude stabilization in finite time. For the fast subsystem, distributed piezoelectric actuators with leader–follower consensus and feedback control are applicable to rapid and stable vibration suppression of the ultra–large structure. Finally, simulation results validate the effectiveness and superiority of these control methods on the satellite, where collaborative control effects on multiple key indices including attitude and vibration control accuracy and settling time are significant. This work facilitates high–accuracy and –stability collaborative control of future ultra–large satellites.

Correlation Analysis of ESG Ratings and Enterprise Performance

ESG (environment, society and governance) evaluation system, as a tool to comprehensively consider the sustainable development ability of enterprises, is increasingly receiving attention. In the context of the promotion of the concept of global sustainable development and the pursuit of high-quality economic development, many third-party evaluation institutions and index research organizations at home and abroad are actively building and improving the ESG rating framework. Through systematic review of domestic and foreign academic circles of ESG rating and enterprise performance correlation research results, this paper reveals an important discovery: ESG rating mechanism not only provides the mirror of self, make it can accurate positioning and optimization in environmental protection, social responsibility and corporate governance, also became the driving enterprises to the direction of more green, harmonious and efficient key force, and promote the long-term sustainable development of the enterprise.

SELF-Former: multi-scale gene filtration transformer for single-cell spatial reconstruction.

The spatial reconstruction of single-cell RNA sequencing (scRNA-seq) data into spatial transcriptomics (ST) is a rapidly evolving field that addresses the significant challenge of aligning gene expression profiles to their spatial origins within tissues. This task is complicated by the inherent batch effects and the need for precise gene expression characterization to accurately reflect spatial information. To address these challenges, we developed SELF-Former, a transformer-based framework that utilizes multi-scale structures to learn gene representations, while designing spatial correlation constraints for the reconstruction of corresponding ST data. SELF-Former excels in recovering the spatial information of ST data and effectively mitigates batch effects between scRNA-seq and ST data. A novel aspect of SELF-Former is the introduction of a gene filtration module, which significantly enhances the spatial reconstruction task by selecting genes that are crucial for accurate spatial positioning and reconstruction. The superior performance and effectiveness of SELF-Former's modules have been validated across four benchmark datasets, establishing it as a robust and effective method for spatial reconstruction tasks. SELF-Former demonstrates its capability to extract meaningful gene expression information from scRNA-seq data and accurately map it to the spatial context of real ST data. Our method represents a significant advancement in the field, offering a reliable approach for spatial reconstruction.

Anti-swing position control of super-twisting sliding mode for underactuated tower crane based on nonlinear marine predator algorithm

Due to the nonlinear, underactuated, and strongly coupled characteristics of tower cranes, issues such as inaccurate load positioning and severe swinging are prone to occur during transportation, making the control problem extremely complex. To address these issues, this paper has designed a super-twisting robust sliding mode controller based on the nonlinear marine predator algorithm (NMPA) to ensure the accurate positioning of the desired location during the transportation process of the tower crane while reducing the oscillation of the load. First, a nonlinear dynamic model of a four-degree-of-freedom tower crane considering friction is constructed. Second, to address the difficulty of effectively controlling the underactuated tower crane system model due to its nonlinearity and strong coupling, the super-twisting algorithm is introduced, and a super-twisting sliding mode controller for anti-swing positioning during the crane transportation process is designed. Then, the parameters of the super-twisting sliding mode controller are optimized using the NMPA to suppress sliding mode chattering and quickly achieve the system’s steady state. Finally, the stability of the nonlinear tower crane system is analyzed using Lyapunov’s theory and LaSalle’s invariance principle to ensure the closed-loop stability of the error dynamics. The simulation results show that the proposed control method exhibits excellent load anti-sway performance and robustness.

Combined BDS/5G seamless positioning scheme based on joint switching strategy of satellite elevation angle and CNR in complex urban environments

Abstract Satellite-based positioning has gained popularity, but in bustling urban areas, signals face challenges like serious attenuation, affecting the reliability of positioning. To overcome this, we propose a seamless positioning approach that combines the BeiDou navigation satellite system (BDS) and 5G, specifically designed for complex urban settings. Initially, we establish static and dynamic positioning solutions using real 5G data measured through the time difference of arrival method, resulting in accurate 5G indoor positioning. Following this, we develop a combined BDS/5G positioning model incorporating joint switching based on satellite elevation angle and carrier-to-noise ratio (CNR). We conduct positioning experiments in intricate environments to validate the effectiveness of our model. The experimental outcomes demonstrate that our combined BDS/5G seamless positioning model, employing the joint switching strategy of satellite elevation angle and CNR, achieves impressive positioning accuracies ranging from decimeters to meters. This approach markedly enhances accuracy and reliability of seamless positioning in challenging urban scenarios.

Study on the detection of power line operation anomalies in the Hexi Corridor based on multi-scale filtering of BeiDou satellite signals

In the artificial intelligence detection of power line anomalies, the identification effect is determined by the positioning process of two-dimensional map, which is also a difficult point in this field Therefore, this paper proposes a method to detect the abnormal operation of power lines in Hexi Corridor based on multi-scale filtering of Beidou satellite signals. Multi-scale processing is carried out by wavelet transform to obtain multiple wavelet basis functions of different scales. On this basis, a two-dimensional time–frequency diagram is drawn according to the results of continuous wavelet transform. The adaptive multi-time frequency entropy method is selected to divide the two-dimensional time–frequency map into multiple layers and scales, and the adaptive multi-scale time–frequency entropy of the time–frequency plane is calculated. After smoothing the obtained power line position signal by S-G filtering method, the power line position signal of Hexi Corridor is obtained by GPS/ Beidou dual-mode satellite positioning system, and the positioning signal is optimized by using the positioning mechanism of multiple receiving stations. Realize the abnormal operation detection of power lines in Hexi Corridor. The experimental results show that this method can obtain more accurate positioning signals, and the geometric accuracy factor GDOP fluctuates in the range of 0 ∼ 2. The unsmooth signal can be effectively removed; The maximum error result of abnormal position detection is 1.22kn；; At the same time, the abnormal displacement section of the line can be determined.

Accurate Low Complexity Quadrature Angular Diversity Aperture Receiver for Visible Light Positioning.

Despite the many potential applications of an accurate indoor positioning system (IPS), no universal, readily available system exists. Much of the IPS research to date has been based on the use of radio transmitters as positioning beacons. Visible light positioning (VLP) instead uses LED lights as beacons. Either cameras or photodiodes (PDs) can be used as VLP receivers, and position estimates are usually based on either the angle of arrival (AOA) or the strength of the received signal. Research on the use of AOA with photodiode receivers has so far been limited by the lack of a suitable compact receiver. The quadrature angular diversity aperture receiver (QADA) can fill this gap. In this paper, we describe a new QADA design that uses only three readily available parts: a quadrant photodiode, a 3D-printed aperture, and a programmable system on a chip (PSoC). Extensive experimental results demonstrate that this design provides accurate AOA estimates within a room-sized test chamber. The flexibility and programmability of the PSoC mean that other sensors can be supported by the same PSoC. This has the potential to allow the AOA estimates from the QADA to be combined with information from other sensors to form future powerful sensor-fusion systems requiring only one beacon.

Real-time tracking of the Bragg peak during proton therapy via 3D protoacoustic Imaging in a clinical scenario

Proton radiotherapy favored over X-ray photon therapy due to its reduced radiation exposure to surrounding healthy tissues, is highly dependent on the accurate positioning of the Bragg peak. Existing methods like PET and prompt gamma imaging to localize Bragg peak face challenges of low precision and high complexity. Here we introduce a 3D protoacoustic imaging with a 2D matrix array of 256 ultrasound transducers compatible with 256 parallel data acquisition channels provides real-time imaging capability (up to 75 frames per second with 10 averages), achieving high precision (5 mm/5% Gamma index shows accuracy better than 95.73%) at depths of tens of centimeters. We have successfully implemented this method in liver treatment with 5 pencil beam scanning and in prostate cancer treatment on a human torso phantom using a clinical proton machine. This demonstrates its capability to accurately identify the Bragg peak in practical clinical scenarios. It paves the way for adaptive radiotherapy with real-time feedback, potentially revolutionizing radiotherapy by enabling closed-loop treatment for improved patient outcomes.

Endoscopic submucosal resection (ESD) and endoscopic full-thickness resection (EFTR) via balloon-assisted enteroscopy (BAE) in small bowel subepithelial lesions: experience in treating fifteen cases.

The study objective was to evaluate the primary feasibility of endoscopic submucosal resection (ESD) and endoscopic full-thickness resection (EFTR) via balloon-assisted enteroscopy (BAE) to treat small bowel subepithelial lesions (SELs). A retrospective case series study was performed. The first fifteen consecutive patients who underwent ESD (n = 10) and EFTR (n = 5) via BAE to remove small bowel SELs from November 2016 to December 2023 were included. The main outcome measures were the technique success rate, operative time and complication rate. This research focused on 15 cases of jejunoileal SELs, four cases of lipomyoma, three cases of ectopic pancreas, two cases of NETs, three cases of benign fibrous tumours and three cases of angioma. The overall technique success rate was 86.7%, with 100% (10/10) and 60% (3/5) for BAE-ESD and BAE-EFTR, respectively, in removing small bowel SELs. Two cases of EFTR failed, as the BAE operation was unsuitable for tumour resection and suture repair of a perforated wound. No serious bleeding or any postoperative complications occurred. The median time of endoscopic resection via BAE for SELs was 44min (range 22-68min). ESD and EFTR via BAE might be alternative choices for treating small SELs in the small bowel, with the advantages of clear and accurate positioning and minimal invasiveness. However, its superiority over surgery still needs to be further investigated.

An Algorithm for Strapdown Airborne Gravity Disturbance Vector Measurement Based on High-Precision Navigation and EGM2008.

Attitude errors, accelerometer bias, the gravity disturbance vector, and their coupling are the primary factors obstructing strapdown airborne vector gravimetry. This paper takes the geocentric inertial frame as a reference and solves the kinematic equations of its motion and its errors of the body frame and local geographic frame in the Lie group, respectively; the attitude accuracy is improved through a high-precision navigation algorithm. The constant accelerometer bias is estimated through Kalman filtering and is deducted from the accelerometer output to eliminate its influence. Based on the EGM2008 model, the low-frequency components of the gravity disturbance vector are corrected. The gravity disturbance vectors after model data fusion were low-pass filtered to obtain the ultimate results. This method was applied to flight experimental data in the South China Sea, and a gravity anomaly accuracy of better than 0.5 mGal, a northward gravity disturbance accuracy of 0.85 mGal, and an eastward gravity disturbance accuracy of 4.0 mGal were obtained, with a spatial resolution of approximately 4.8 km.

Effect of Extracorporeal Shock Wave on IGF-1, TNF-α, and IL-1in Joint Fluid of Patients with Temporomandibular Joint Disorder Syndrome.

As a new therapeutic method, extracorporeal shock wave (ESW) has shown remarkable efficacy in the treatment of temporomandibular joint disorder syndrome. Numerous studies have shown that it has the advantages of noninvasiveness, short treatment time, etc. It can effectively relieve pain and improve symptoms such as joint mobility and opening degree. In clinical practice, through accurate diagnosis and positioning of different patients, appropriate treatment parameters such as therapeutic transducer, frequency and pressure can be selected to significantly improve the efficacy. At the same time, follow-up evaluation after treatment, including temporomandibular joint disorder index and visual analogue score, is also helpful to fully understand the rehabilitation of patients. Extracorporeal shock wave therapy (ESWT) brings new hope to patients with temporomandibular joint disorder syndrome and has a broad application prospect.

Application of IMU/GPS Integrated Navigation System Based on Adaptive Unscented Kalman Filter Algorithm in 3D Positioning of Forest Rescue Personnel.

Utilizing reliable and accurate positioning and navigation systems is crucial for saving the lives of rescue personnel and accelerating rescue operations. However, Global Navigation Satellite Systems (GNSSs), such as GPS, may not provide stable signals in dense forests. Therefore, integrating multiple sensors like GPS and Inertial Measurement Units (IMUs) becomes essential to enhance the availability and accuracy of positioning systems. To accurately estimate rescuers' positions, this paper employs the Adaptive Unscented Kalman Filter (AUKF) algorithm with measurement noise variance matrix adaptation, integrating IMU and GPS data alongside barometric altitude measurements for precise three-dimensional positioning in complex environments. The AUKF enhances estimation robustness through the adaptive adjustment of the measurement noise variance matrix, particularly excelling when GPS signals are interrupted. This study conducted tests on two-dimensional and three-dimensional road scenarios in forest environments, confirming that the AUKF-algorithm-based integrated navigation system outperforms the traditional Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Adaptive Extended Kalman Filter (AEKF) in emergency rescue applications. The tests further evaluated the system's navigation performance on rugged roads and during GPS signal interruptions. The results demonstrate that the system achieves higher positioning accuracy on rugged forest roads, notably reducing errors by 18.32% in the north direction, 8.51% in the up direction, and 3.85% in the east direction compared to the EKF. Furthermore, the system exhibits good adaptability during GPS signal interruptions, ensuring continuous and accurate personnel positioning during rescue operations.

A novel advanced hybrid fuzzy MPPT controllers for renewable energy systems

At present, the availability of nonrenewable sources and their usage for electric vehicle technology is reducing gradually because of their disadvantages are more environmental pollution, direct effect on human health, less reliability, and taking more time to start functioning. So, in this article, the proton exchange membrane fuel cell (PEMFC) is considered for the automotive application because of its advantages quick startup, more power density, more safety to handle, high efficiency, and capability of operating at very low operational temperature conditions. However, the drawback of PEMFC is very difficult to identify the accurate MPP position of the fuel system. Here, the improved variable step genetic algorithm is added with the adaptive neuro-fuzzy inference system for tracking the operational point of the proposed system with high efficiency. These hybrid MPPT controller features are easy to understand, more accurate, have a better dynamic response, and have low design complexity. The evaluated proposed MPPT controller operational efficiency, and settling time of the converter voltage at different fuel stack temperature conditions are 98.7402%, and 0.01607 s respectively. Finally, the boost converter is used in this work to enhance the voltage supply capability of the entire system. The proposed system is investigated by applying the MATLAB tool.

Integrated Scale-Adaptive Adjustment Factor-Enhanced BlendMask Method for Pineapple Processing System

This study addresses the challenge of efficiently peeling pineapples, which have a distinct elliptical form, thick skin, and small eyes that are difficult to detect with conventional automated methods. This results in significant flesh waste. To improve the process, we developed an integrated system combining an enhanced BlendMask method, termed SAAF-BlendMask, and a Pose Correction Planning (PCP) method. SAAF-BlendMask improves the detection of small pineapple eyes, while PCP ensures accurate posture adjustment for precise path planning. The system uses 3D vision and deep learning technologies, achieving an average precision (AP) of 73.04% and a small object precision (APs) of 62.54% in eye detection, with a path planning success rate reaching 99%. The fully automated electromechanical system was tested on 110 real pineapples, demonstrating a reduction in flesh waste by 11.7% compared to traditional methods. This study highlights the potential of advanced machine vision and robotics in enhancing the efficiency and precision of food processing.