The Successive Orthogonalization Decentralized Kalman Filter (SODKF ) is a new method which is used for large system state estimation. It can be applied not only to large system decentralization, but also to precisi...The Successive Orthogonalization Decentralized Kalman Filter (SODKF ) is a new method which is used for large system state estimation. It can be applied not only to large system decentralization, but also to precision realization at approximately the same level of the global filter, thus, making possible the engineering operation as well as shortening the computing time. This paper discusses the principles and features of SODKF when used in GPS/INS integrated navigation system. The system will be firstly divided into three subsystems and then corrected in both open and closed loops. The system simulation results by two integrated patterns show that SODKF is efficient and realizable. While the three subsystems are simulated in series, the computing speed doubles that of the global system. In addition, its optimal estimating precision remains unchanged. It can be concluded from this paper that large integrated navigation systems with GPS, INS, Terrain Match, Loran C, Doppler Radar and Radio Altimeter can be made more efficient by this multi subsystem of navigation.展开更多
Background and Objective Electromagnetic navigation technology has demonstrated significant potential in enhancing the accuracy and safety of neurosurgical procedures.However,traditional electromagnetic navigation sys...Background and Objective Electromagnetic navigation technology has demonstrated significant potential in enhancing the accuracy and safety of neurosurgical procedures.However,traditional electromagnetic navigation systems face challenges such as high equipment costs,complex operation,bulky size,and insufficient anti-interference performance.To address these limitations,our study developed and validated a novel portable electromagnetic neuronavigation system designed to improve the precision,accessibility,and clinical applicability of electromagnetic navigation technology in cranial surgery.Methods The software and hardware architecture of a portable neural magnetic navigation system was designed.The key technologies of the system were analysed,including electromagnetic positioning algorithms,miniaturized sensor design,optimization of electromagnetic positioning and navigation algorithms,anti-interference signal processing methods,and fast three-dimensional reconstruction algorithms.A prototype was developed,and its accuracy was tested.Finally,a preliminary clinical application evaluation was conducted.Results This study successfully developed a comprehensive portable electromagnetic neuronavigation system capable of achieving preoperative planning,intraoperative real-time positioning and navigation,and postoperative evaluation of navigation outcomes.Through rigorous collaborative testing of the system’s software and hardware,the accuracy of electromagnetic neuronavigation has been validated to meet clinical requirements.Conclusions This study developed a portable neuroelectromagnetic navigation system and validated its effectiveness and safety through rigorous model testing and preliminary clinical applications.The system is characterized by its compact size,high precision,excellent portability,and user-friendly operation,making it highly valuable for promoting navigation technology and advancing the precision and minimally invasive nature of neurosurgical procedures.展开更多
Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including at...Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including atmospheric, hydrological, and nontidal ocean loading. Continuous improvements in the accuracy of surface mass loading products, performance of Earth models, and precise data-processing technologies have significantly advanced research on the effects of environmental loading on nonlinear variations in GNSS coordinate time series. However, owing to theoretical limitations, the lack of high spatiotemporal resolution surface mass observations, and the coupling of GNSS technology-related systematic errors, environmental loading and nonlinear GNSS reference station displacements remain inconsistent. The applicability and capability of these loading products across different regions also require further evaluation. This paper outlines methods for modeling environmental loading, surface mass loading products, and service organizations. In addition, it summarizes recent advances in applying environmental loading to address nonlinear variations in global and regional GNSS coordinate time series. Moreover, the scientific questions of existing studies are summarized, and insights into future research directions are provided. The complex nonlinear motion of reference stations is a major factor limiting the accuracy of the current terrestrial reference frame. Further refining the environmental load modeling method, establishing a surface mass distribution model with high spatiotemporal resolution and reliability, exploring other environmental load factors such as ice sheet and artificial mass-change effects, and developing an optimal data-processing model and strategy for reprocessing global reference station data consistently could contribute to the development of a millimeter-level nonlinear motion model for GNSS reference stations with actual physical significance and provide theoretical support for establishing a terrestrial reference frame with 1 mm accuracy by 2050.展开更多
Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively r...Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.展开更多
Fluorescence imaging in the second near-infrared window(NIR-II,900-1880 nm)offers high signalto-background ratio(SBR),enhanced definition,and superior tissue penetration,making it ideal for real-time surgical navigati...Fluorescence imaging in the second near-infrared window(NIR-II,900-1880 nm)offers high signalto-background ratio(SBR),enhanced definition,and superior tissue penetration,making it ideal for real-time surgical navigation.However,with single-channel imaging,surgeons must frequently switch between the surgi⁃cal field and the NIR-II images on the monitor.To address this,a coaxial dual-channel imaging system that com⁃bines visible light and 1100 nm longpass(1100LP)fluorescence was developed.The system features a custom⁃ized coaxial dual-channel lens with optimized distortion,achieving precise alignment with an error of less than±0.15 mm.Additionally,the shared focusing mechanism simplifies operation.Using FDA-approved indocya⁃nine green(ICG),the system was successfully applied in dual-channel guided rat lymph node excision,and blood supply assessment of reconstructed human flap.This approach enhances surgical precision,improves opera⁃tional efficiency,and provides a valuable reference for further clinical translation of NIR-II fluorescence imaging.展开更多
With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation wind...With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.展开更多
1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become ...1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become one of the current research hotspots in spacecraft autonomous navigation. Spacecraft face complex electromagnetic interference in orbit. The time-varying, non-Gaussian interference from internal devices and external environment can lead to measurement distortion.展开更多
In order to address the challenges encountered in visual navigation for asteroid landing using traditional point features,such as significant recognition and extraction errors,low computational efficiency,and limited ...In order to address the challenges encountered in visual navigation for asteroid landing using traditional point features,such as significant recognition and extraction errors,low computational efficiency,and limited navigation accuracy,a novel approach for multi-type fusion visual navigation is proposed.This method aims to overcome the limitations of single-type features and enhance navigation accuracy.Analytical criteria for selecting multi-type features are introduced,which simultaneously improve computational efficiency and system navigation accuracy.Concerning pose estimation,both absolute and relative pose estimation methods based on multi-type feature fusion are proposed,and multi-type feature normalization is established,which significantly improves system navigation accuracy and lays the groundwork for flexible application of joint absolute-relative estimation.The feasibility and effectiveness of the proposed method are validated through simulation experiments through 4769 Castalia.展开更多
As the core information infrastructure of modern information warfare,the offensive and defensive confrontations of satellite navigation systems have given rise to navigation warfare,which focuses on seizing control of...As the core information infrastructure of modern information warfare,the offensive and defensive confrontations of satellite navigation systems have given rise to navigation warfare,which focuses on seizing control of navigation resources.Based on the space segment,control segment,and user segment of satellite navigation systems,this paper systematically constructs an offensive-defensive technology system for navigation warfare,and deeply analyzes core measures such as signal enhancement and suppression,autonomous navigation and link jamming,anti-jamming reception,and integrated navigation.It extracts key technologies including adaptive nulling antennas,joint filtering,and multi-dimensional combined jamming,and discusses the technical effectiveness of these technologies by incorporating relevant cases.The advantages of navigation warfare stem from multi-segment coordination and technological inte-gration.In the future,the development directions of navigation warfare will focus on three aspects:enhancing satellite capabilities,tackling core technical challenges,and building a multi-dimensional system.展开更多
This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification metho...This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification methodology for practical implementation of vision-based navigation technology on the microsatellite platform.Firstly,a low power consumption,light weight,and high performance vision-based relative navigation optical sensor is designed.Subsequently,a set of ground verification system is designed for the hardware-in-the-loop testing of the vision-based relative navigation systems.Finally,the designed vision-based relative navigation optical sensor and the proposed angles-only navigation algorithms are tested on the ground verification system.The results verify that the optical simulator after geometrical calibration can meet the requirements of the hardware-in-the-loop testing of vision-based relative navigation systems.Based on experimental results,the relative position accuracy of the angles-only navigation filter at terminal time is increased by 25.5%,and the relative speed accuracy is increased by 31.3% compared with those of optical simulator before geometrical calibration.展开更多
The Global Navigation Satellite System(GNSS)has been widely adopted in numerous fields,including intelligent transportation,remote sensing,and aeronautical and astronautical engineering.As new navigation approaches,te...The Global Navigation Satellite System(GNSS)has been widely adopted in numerous fields,including intelligent transportation,remote sensing,and aeronautical and astronautical engineering.As new navigation approaches,technologies,and applications continue to emerge,they attract significant global attention.Ensuring reliable positioning solutions with high accuracy,strong anti-interference capabilities,high availability and low integrity risks has become increasingly critical.展开更多
Objective:To observe the guiding role of image navigation technology in the treatment of patients with tuberculosis.Methods:A total of 188 patients with multidrug-resistant tuberculosis(MDR-TB)and rifampin-resistant t...Objective:To observe the guiding role of image navigation technology in the treatment of patients with tuberculosis.Methods:A total of 188 patients with multidrug-resistant tuberculosis(MDR-TB)and rifampin-resistant tuberculosis(RR-TB)who were hospitalized in the hospital from September 2023 to September 2024 were included.After random equal division,94 patients were included in the control group and received systemic anti-tuberculosis chemotherapy;94 patients were included in the treatment group.Based on systemic anti-tuberculosis treatment,digital subtraction angiography(DSA)technology was used to inject targeted drugs into the bronchial lumen through bronchoscopy to complete anti-tuberculosis treatment.The changes in sputum bacteria and imaging were observed in the two groups.Results:The sputum negative conversion rate in the treatment group was significantly higher than that in the control group(86.2%;70.2%)(u=2.74,P<0.01).The absorption rate of CT imaging lesions(significant absorption)was significantly higher than that of the control group(83.0%;50%)(u=2.45,P<0.05).The closure rate of chest CT cavities was significantly higher than that of the control group(74.2%;39.1%)(u=2.20,P<0.05).During the treatment process,the improvement of clinical symptoms was significantly higher than that of the control group,and the difference was statistically significant.There was no statistically significant difference in the incidence of adverse reactions between the two groups(x^(2)=0.434,P>0.05).Conclusion:Based on DSA,targeted drug infusion within the bronchoscope can significantly improve the efficacy of the disease,with mild adverse reactions that patients can tolerate.It is worthy of promotion and application.展开更多
In multiple Unmanned Aerial Vehicles(UAV)systems,achieving efficient navigation is essential for executing complex tasks and enhancing autonomy.Traditional navigation methods depend on predefined control strategies an...In multiple Unmanned Aerial Vehicles(UAV)systems,achieving efficient navigation is essential for executing complex tasks and enhancing autonomy.Traditional navigation methods depend on predefined control strategies and trajectory planning and often perform poorly in complex environments.To improve the UAV-environment interaction efficiency,this study proposes a multi-UAV integrated navigation algorithm based on Deep Reinforcement Learning(DRL).This algorithm integrates the Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),and Visual Navigation System(VNS)for comprehensive information fusion.Specifically,an improved multi-UAV integrated navigation algorithm called Information Fusion with MultiAgent Deep Deterministic Policy Gradient(IF-MADDPG)was developed.This algorithm enables UAVs to learn collaboratively and optimize their flight trajectories in real time.Through simulations and experiments,test scenarios in GNSS-denied environments were constructed to evaluate the effectiveness of the algorithm.The experimental results demonstrate that the IF-MADDPG algorithm significantly enhances the collaborative navigation capabilities of multiple UAVs in formation maintenance and GNSS-denied environments.Additionally,it has advantages in terms of mission completion time.This study provides a novel approach for efficient collaboration in multi-UAV systems,which significantly improves the robustness and adaptability of navigation systems.展开更多
Since its inception in the 1960s,light detection and ranging(LiDAR)technology has demonstrated great potential in various fields such as autonomous driving,robot navigation,and environmental monitoring due to its high...Since its inception in the 1960s,light detection and ranging(LiDAR)technology has demonstrated great potential in various fields such as autonomous driving,robot navigation,and environmental monitoring due to its high precision,high resolution,and strong anti-interference capability.This paper reviews the development history,technical principles,application fields,and future development trends of LiDAR technology.It introduces the technical applications of LiDAR technology in autonomous driving,robot navigation,and environmental monitoring,and explores the development direction of SLAM algorithms in multi-sensor fusion and real-time map construction,providing a reference basis for the development and research of LiDAR.展开更多
Robot navigation in complex crowd service scenarios,such as medical logistics and commercial guidance,requires a dynamic balance between safety and efficiency,while the traditional fixed reward mechanism lacks environ...Robot navigation in complex crowd service scenarios,such as medical logistics and commercial guidance,requires a dynamic balance between safety and efficiency,while the traditional fixed reward mechanism lacks environmental adaptability and struggles to adapt to the variability of crowd density and pedestrian motion patterns.This paper proposes a navigation method that integrates spatiotemporal risk field modeling and adaptive reward optimization,aiming to improve the robot’s decision-making ability in diverse crowd scenarios through dynamic risk assessment and nonlinear weight adjustment.We construct a spatiotemporal risk field model based on a Gaussian kernel function by combining crowd density,relative distance,andmotion speed to quantify environmental complexity and realize crowd-density-sensitive risk assessment dynamically.We apply an exponential decay function to reward design to address the linear conflict problem of fixed weights in multi-objective optimization.We adaptively adjust weight allocation between safety constraints and navigation efficiency based on real-time risk values,prioritizing safety in highly dense areas and navigation efficiency in sparse areas.Experimental results show that our method improves the navigation success rate by 9.0%over state-of-the-art models in high-density scenarios,with a 10.7%reduction in intrusion time ratio.Simulation comparisons validate the risk field model’s ability to capture risk superposition effects in dense scenarios and the suppression of near-field dangerous behaviors by the exponential decay mechanism.Our parametric optimization paradigm establishes an explicit mapping between navigation objectives and risk parameters through rigorous mathematical formalization,providing an interpretable approach for safe deployment of service robots in dynamic environments.展开更多
Instantaneous Global Navigation Satellite System(GNSS)attitude determination method which achieves real-time attitude determination using GNSS signal has been extensively studied,particularly the one using a priori at...Instantaneous Global Navigation Satellite System(GNSS)attitude determination method which achieves real-time attitude determination using GNSS signal has been extensively studied,particularly the one using a priori attitude information replacing the code measurements to enhance the successful rate for ambiguity resolution.However,there exists a key limitation that this method relies on considerable Monte Carlo sampling particles to construct the pdf of ambiguities,resulting in significant computational burdens.To address this limitation,this paper provides a rapid single-epoch GNSS attitude determination method based on a priori attitude information.It utilizes a second-order Taylor expansion to analytically estimate the covariance of the baseline conditioned on a priori attitude information.This is followed by deriving the float solution and covariance of ambiguities,which are then processed using the standard LAMBDA method for integer ambiguity resolution.Experimental results demonstrate that our method is both efficient and accurate,significantly reducing computational costs compared to previous methods,thereby enhancing its applicability for GNSS-based attitude determination.展开更多
Aiming at the missile avoidance problem of the unmanned aerial vehicle(UAV)in complex obstacle environments,this work proposes a collision-avoidance method based on receding horizon optimization.The proposed method ge...Aiming at the missile avoidance problem of the unmanned aerial vehicle(UAV)in complex obstacle environments,this work proposes a collision-avoidance method based on receding horizon optimization.The proposed method generated a specific trajectory for the UAV to effectively induce the proportional navigation missile to successfully intercept the obstacle,thereby accomplishing the evasive maneuver.The evasive maneuver was divided into two distinct stages,namely the collision-inducing phase and the fast departure phase.The obstacle potential field-based target selection algorithm was employed to identify the most appropriate target obstacle,while the induced trajectory was determined through a combination of receding horizon optimization and the hp-adaptive pseudo-spectral method.Simulation experiments were carried out under three different types of obstacle environments and one multiobstacle environment,and the simulation results show that the method proposed in this paper greatly improves the success rate of UAV evasive maneuvers,proving the effectiveness of this method.展开更多
The Titanic sunk 113 years ago on April 14-15,after hitting an iceberg,with human error likely causing the ship to wander into those dangerous waters.Today,autonomous systems built on AI can help ships avoid such acci...The Titanic sunk 113 years ago on April 14-15,after hitting an iceberg,with human error likely causing the ship to wander into those dangerous waters.Today,autonomous systems built on AI can help ships avoid such accidents.But could such a system explain to the captain why it was controlling the ship in a certain way?展开更多
Mobile robots represented by smart wheelchairs can assist elderly people with mobility difficulties.This paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,wh...Mobile robots represented by smart wheelchairs can assist elderly people with mobility difficulties.This paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior maps.In order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic goals.At last,comparative experiments were carried out in the real environment.Results show that our method is superior in terms of safety,comfort and docking accuracy.展开更多
The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor env...The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor environments and radio signal interference caused by multiwall environments,which collectively lead to significant positioning errors,vision-based positioning has emerged as a crucial method in indoor positioning research.This paper introduces a scale hierarchical matching model to tackle challenges associated with large visual databases and high scene similarity,both of which will compromise matching accuracy and lead to prolonged positioning delays.The proposed model establishes an image feature database using GIST features and speeded up robust feature(SURF)in the offline stage.In the online stage,a positioning navigating algorithm is constructed based on Dijkstra’s path planning.Additionally,a corresponding Android application has been developed to facilitate visual positioning and navigation in indoor environments.Experimental results obtained in real indoor environments demonstrate that the proposed method significantly enhances positioning accuracy compared with similar algorithms,while effectively reducing time overhead.This improvement caters to the requirements for indoor positioning and navigation,thereby meeting user needs.展开更多
文摘The Successive Orthogonalization Decentralized Kalman Filter (SODKF ) is a new method which is used for large system state estimation. It can be applied not only to large system decentralization, but also to precision realization at approximately the same level of the global filter, thus, making possible the engineering operation as well as shortening the computing time. This paper discusses the principles and features of SODKF when used in GPS/INS integrated navigation system. The system will be firstly divided into three subsystems and then corrected in both open and closed loops. The system simulation results by two integrated patterns show that SODKF is efficient and realizable. While the three subsystems are simulated in series, the computing speed doubles that of the global system. In addition, its optimal estimating precision remains unchanged. It can be concluded from this paper that large integrated navigation systems with GPS, INS, Terrain Match, Loran C, Doppler Radar and Radio Altimeter can be made more efficient by this multi subsystem of navigation.
基金funded by National Natural Science Foundation of China(No.82272134)Innovative Research Group Project of the National Natural Science Foundation of China(No.82272134,Xiao-lei Chen).
文摘Background and Objective Electromagnetic navigation technology has demonstrated significant potential in enhancing the accuracy and safety of neurosurgical procedures.However,traditional electromagnetic navigation systems face challenges such as high equipment costs,complex operation,bulky size,and insufficient anti-interference performance.To address these limitations,our study developed and validated a novel portable electromagnetic neuronavigation system designed to improve the precision,accessibility,and clinical applicability of electromagnetic navigation technology in cranial surgery.Methods The software and hardware architecture of a portable neural magnetic navigation system was designed.The key technologies of the system were analysed,including electromagnetic positioning algorithms,miniaturized sensor design,optimization of electromagnetic positioning and navigation algorithms,anti-interference signal processing methods,and fast three-dimensional reconstruction algorithms.A prototype was developed,and its accuracy was tested.Finally,a preliminary clinical application evaluation was conducted.Results This study successfully developed a comprehensive portable electromagnetic neuronavigation system capable of achieving preoperative planning,intraoperative real-time positioning and navigation,and postoperative evaluation of navigation outcomes.Through rigorous collaborative testing of the system’s software and hardware,the accuracy of electromagnetic neuronavigation has been validated to meet clinical requirements.Conclusions This study developed a portable neuroelectromagnetic navigation system and validated its effectiveness and safety through rigorous model testing and preliminary clinical applications.The system is characterized by its compact size,high precision,excellent portability,and user-friendly operation,making it highly valuable for promoting navigation technology and advancing the precision and minimally invasive nature of neurosurgical procedures.
基金supported by the Basic Science Center Project of the National Natural Science Foundation of China(42388102)the National Natural Science Foundation of China(42174030)+2 种基金the Special Fund of Hubei Luojia Laboratory(220100020)the Major Science and Technology Program for Hubei Province(2022AAA002)the Fundamental Research Funds for the Central Universities of China(2042022dx0001 and 2042023kfyq01)。
文摘Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including atmospheric, hydrological, and nontidal ocean loading. Continuous improvements in the accuracy of surface mass loading products, performance of Earth models, and precise data-processing technologies have significantly advanced research on the effects of environmental loading on nonlinear variations in GNSS coordinate time series. However, owing to theoretical limitations, the lack of high spatiotemporal resolution surface mass observations, and the coupling of GNSS technology-related systematic errors, environmental loading and nonlinear GNSS reference station displacements remain inconsistent. The applicability and capability of these loading products across different regions also require further evaluation. This paper outlines methods for modeling environmental loading, surface mass loading products, and service organizations. In addition, it summarizes recent advances in applying environmental loading to address nonlinear variations in global and regional GNSS coordinate time series. Moreover, the scientific questions of existing studies are summarized, and insights into future research directions are provided. The complex nonlinear motion of reference stations is a major factor limiting the accuracy of the current terrestrial reference frame. Further refining the environmental load modeling method, establishing a surface mass distribution model with high spatiotemporal resolution and reliability, exploring other environmental load factors such as ice sheet and artificial mass-change effects, and developing an optimal data-processing model and strategy for reprocessing global reference station data consistently could contribute to the development of a millimeter-level nonlinear motion model for GNSS reference stations with actual physical significance and provide theoretical support for establishing a terrestrial reference frame with 1 mm accuracy by 2050.
文摘Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.
基金Supported by the National Natural Science Foundation of China(U23A20487)the National Key R&D Program of China(2022YFB3206000)+1 种基金Dr.Li Dak Sum&Yip Yio Chin Development Fund for Regenerative Medicine,Zhejiang Universitythe National Natural Science Foundation of China(61975172).
文摘Fluorescence imaging in the second near-infrared window(NIR-II,900-1880 nm)offers high signalto-background ratio(SBR),enhanced definition,and superior tissue penetration,making it ideal for real-time surgical navigation.However,with single-channel imaging,surgeons must frequently switch between the surgi⁃cal field and the NIR-II images on the monitor.To address this,a coaxial dual-channel imaging system that com⁃bines visible light and 1100 nm longpass(1100LP)fluorescence was developed.The system features a custom⁃ized coaxial dual-channel lens with optimized distortion,achieving precise alignment with an error of less than±0.15 mm.Additionally,the shared focusing mechanism simplifies operation.Using FDA-approved indocya⁃nine green(ICG),the system was successfully applied in dual-channel guided rat lymph node excision,and blood supply assessment of reconstructed human flap.This approach enhances surgical precision,improves opera⁃tional efficiency,and provides a valuable reference for further clinical translation of NIR-II fluorescence imaging.
文摘With the increase of international trade activities and the gradual melting of the polar ice cap,the importance of the Arctic route for marine transportation has been emphasized.Prediction of the polar navigation window period is crucial for navigating in the Arctic route,which is of great significance to the selection of the route and the optimization of navigation.This paper introduces the establishment of a risk index system,determination of risk index weight,establishment of a risk evaluation model,and prediction algorithm for the window period.In addition,data sources of both environmental factors and ship factors are introducted,and their shortcomings are analyzed,followed by introduction of various methods involved in window prediction and analysis of their advantages and disadvantages.The quantitative risk evaluation and window period algorithm can provide a reference for the research of polar navigation window period prediction.
基金supported by the National Level Project of China (No. 2020-JCJQ-ZQ-059)。
文摘1. Introduction Celestial navigation is a kind of navigation with a long history.With the increasing demand for intelligent autonomy and antielectromagnetic interference in spacecraft, celestial navigation has become one of the current research hotspots in spacecraft autonomous navigation. Spacecraft face complex electromagnetic interference in orbit. The time-varying, non-Gaussian interference from internal devices and external environment can lead to measurement distortion.
基金supported by the National Natural Science Foundation of China(No.U2037602)。
文摘In order to address the challenges encountered in visual navigation for asteroid landing using traditional point features,such as significant recognition and extraction errors,low computational efficiency,and limited navigation accuracy,a novel approach for multi-type fusion visual navigation is proposed.This method aims to overcome the limitations of single-type features and enhance navigation accuracy.Analytical criteria for selecting multi-type features are introduced,which simultaneously improve computational efficiency and system navigation accuracy.Concerning pose estimation,both absolute and relative pose estimation methods based on multi-type feature fusion are proposed,and multi-type feature normalization is established,which significantly improves system navigation accuracy and lays the groundwork for flexible application of joint absolute-relative estimation.The feasibility and effectiveness of the proposed method are validated through simulation experiments through 4769 Castalia.
文摘As the core information infrastructure of modern information warfare,the offensive and defensive confrontations of satellite navigation systems have given rise to navigation warfare,which focuses on seizing control of navigation resources.Based on the space segment,control segment,and user segment of satellite navigation systems,this paper systematically constructs an offensive-defensive technology system for navigation warfare,and deeply analyzes core measures such as signal enhancement and suppression,autonomous navigation and link jamming,anti-jamming reception,and integrated navigation.It extracts key technologies including adaptive nulling antennas,joint filtering,and multi-dimensional combined jamming,and discusses the technical effectiveness of these technologies by incorporating relevant cases.The advantages of navigation warfare stem from multi-segment coordination and technological inte-gration.In the future,the development directions of navigation warfare will focus on three aspects:enhancing satellite capabilities,tackling core technical challenges,and building a multi-dimensional system.
基金supported in part by the Doctoral Initiation Fund of Nanchang Hangkong University(No.EA202403107)Jiangxi Province Early Career Youth Science and Technology Talent Training Project(No.CK202403509).
文摘This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification methodology for practical implementation of vision-based navigation technology on the microsatellite platform.Firstly,a low power consumption,light weight,and high performance vision-based relative navigation optical sensor is designed.Subsequently,a set of ground verification system is designed for the hardware-in-the-loop testing of the vision-based relative navigation systems.Finally,the designed vision-based relative navigation optical sensor and the proposed angles-only navigation algorithms are tested on the ground verification system.The results verify that the optical simulator after geometrical calibration can meet the requirements of the hardware-in-the-loop testing of vision-based relative navigation systems.Based on experimental results,the relative position accuracy of the angles-only navigation filter at terminal time is increased by 25.5%,and the relative speed accuracy is increased by 31.3% compared with those of optical simulator before geometrical calibration.
文摘The Global Navigation Satellite System(GNSS)has been widely adopted in numerous fields,including intelligent transportation,remote sensing,and aeronautical and astronautical engineering.As new navigation approaches,technologies,and applications continue to emerge,they attract significant global attention.Ensuring reliable positioning solutions with high accuracy,strong anti-interference capabilities,high availability and low integrity risks has become increasingly critical.
基金Science and Education Department Harbin Health Committee Project。
文摘Objective:To observe the guiding role of image navigation technology in the treatment of patients with tuberculosis.Methods:A total of 188 patients with multidrug-resistant tuberculosis(MDR-TB)and rifampin-resistant tuberculosis(RR-TB)who were hospitalized in the hospital from September 2023 to September 2024 were included.After random equal division,94 patients were included in the control group and received systemic anti-tuberculosis chemotherapy;94 patients were included in the treatment group.Based on systemic anti-tuberculosis treatment,digital subtraction angiography(DSA)technology was used to inject targeted drugs into the bronchial lumen through bronchoscopy to complete anti-tuberculosis treatment.The changes in sputum bacteria and imaging were observed in the two groups.Results:The sputum negative conversion rate in the treatment group was significantly higher than that in the control group(86.2%;70.2%)(u=2.74,P<0.01).The absorption rate of CT imaging lesions(significant absorption)was significantly higher than that of the control group(83.0%;50%)(u=2.45,P<0.05).The closure rate of chest CT cavities was significantly higher than that of the control group(74.2%;39.1%)(u=2.20,P<0.05).During the treatment process,the improvement of clinical symptoms was significantly higher than that of the control group,and the difference was statistically significant.There was no statistically significant difference in the incidence of adverse reactions between the two groups(x^(2)=0.434,P>0.05).Conclusion:Based on DSA,targeted drug infusion within the bronchoscope can significantly improve the efficacy of the disease,with mild adverse reactions that patients can tolerate.It is worthy of promotion and application.
基金co-supported by the National Natural Science Foundation of China(Nos.92371201 and 52192633)the Natural Science Foundation of Shaanxi Province of China(No.2022JC-03)the Aeronautical Science Foundation of China(No.ASFC-20220019070002)。
文摘In multiple Unmanned Aerial Vehicles(UAV)systems,achieving efficient navigation is essential for executing complex tasks and enhancing autonomy.Traditional navigation methods depend on predefined control strategies and trajectory planning and often perform poorly in complex environments.To improve the UAV-environment interaction efficiency,this study proposes a multi-UAV integrated navigation algorithm based on Deep Reinforcement Learning(DRL).This algorithm integrates the Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),and Visual Navigation System(VNS)for comprehensive information fusion.Specifically,an improved multi-UAV integrated navigation algorithm called Information Fusion with MultiAgent Deep Deterministic Policy Gradient(IF-MADDPG)was developed.This algorithm enables UAVs to learn collaboratively and optimize their flight trajectories in real time.Through simulations and experiments,test scenarios in GNSS-denied environments were constructed to evaluate the effectiveness of the algorithm.The experimental results demonstrate that the IF-MADDPG algorithm significantly enhances the collaborative navigation capabilities of multiple UAVs in formation maintenance and GNSS-denied environments.Additionally,it has advantages in terms of mission completion time.This study provides a novel approach for efficient collaboration in multi-UAV systems,which significantly improves the robustness and adaptability of navigation systems.
文摘Since its inception in the 1960s,light detection and ranging(LiDAR)technology has demonstrated great potential in various fields such as autonomous driving,robot navigation,and environmental monitoring due to its high precision,high resolution,and strong anti-interference capability.This paper reviews the development history,technical principles,application fields,and future development trends of LiDAR technology.It introduces the technical applications of LiDAR technology in autonomous driving,robot navigation,and environmental monitoring,and explores the development direction of SLAM algorithms in multi-sensor fusion and real-time map construction,providing a reference basis for the development and research of LiDAR.
基金supported by the Sichuan Science and Technology Program(2025ZNSFSC0005).
文摘Robot navigation in complex crowd service scenarios,such as medical logistics and commercial guidance,requires a dynamic balance between safety and efficiency,while the traditional fixed reward mechanism lacks environmental adaptability and struggles to adapt to the variability of crowd density and pedestrian motion patterns.This paper proposes a navigation method that integrates spatiotemporal risk field modeling and adaptive reward optimization,aiming to improve the robot’s decision-making ability in diverse crowd scenarios through dynamic risk assessment and nonlinear weight adjustment.We construct a spatiotemporal risk field model based on a Gaussian kernel function by combining crowd density,relative distance,andmotion speed to quantify environmental complexity and realize crowd-density-sensitive risk assessment dynamically.We apply an exponential decay function to reward design to address the linear conflict problem of fixed weights in multi-objective optimization.We adaptively adjust weight allocation between safety constraints and navigation efficiency based on real-time risk values,prioritizing safety in highly dense areas and navigation efficiency in sparse areas.Experimental results show that our method improves the navigation success rate by 9.0%over state-of-the-art models in high-density scenarios,with a 10.7%reduction in intrusion time ratio.Simulation comparisons validate the risk field model’s ability to capture risk superposition effects in dense scenarios and the suppression of near-field dangerous behaviors by the exponential decay mechanism.Our parametric optimization paradigm establishes an explicit mapping between navigation objectives and risk parameters through rigorous mathematical formalization,providing an interpretable approach for safe deployment of service robots in dynamic environments.
基金supported by the Research Grants Council of the Hong Kong Special Administrative Region,China(Nos.25202520,15214523)the Fundamental Research Funds for the Central Universities,China(No.YWF-22-L-805)。
文摘Instantaneous Global Navigation Satellite System(GNSS)attitude determination method which achieves real-time attitude determination using GNSS signal has been extensively studied,particularly the one using a priori attitude information replacing the code measurements to enhance the successful rate for ambiguity resolution.However,there exists a key limitation that this method relies on considerable Monte Carlo sampling particles to construct the pdf of ambiguities,resulting in significant computational burdens.To address this limitation,this paper provides a rapid single-epoch GNSS attitude determination method based on a priori attitude information.It utilizes a second-order Taylor expansion to analytically estimate the covariance of the baseline conditioned on a priori attitude information.This is followed by deriving the float solution and covariance of ambiguities,which are then processed using the standard LAMBDA method for integer ambiguity resolution.Experimental results demonstrate that our method is both efficient and accurate,significantly reducing computational costs compared to previous methods,thereby enhancing its applicability for GNSS-based attitude determination.
基金Natural Science Foundation of Heilongjiang Province of China(Grant No.YQ2022F012)the Fundamental Research Funds for the Central Universities(Grant No.HIT.OCEF.2023010)to provide fund for conducting experiments.
文摘Aiming at the missile avoidance problem of the unmanned aerial vehicle(UAV)in complex obstacle environments,this work proposes a collision-avoidance method based on receding horizon optimization.The proposed method generated a specific trajectory for the UAV to effectively induce the proportional navigation missile to successfully intercept the obstacle,thereby accomplishing the evasive maneuver.The evasive maneuver was divided into two distinct stages,namely the collision-inducing phase and the fast departure phase.The obstacle potential field-based target selection algorithm was employed to identify the most appropriate target obstacle,while the induced trajectory was determined through a combination of receding horizon optimization and the hp-adaptive pseudo-spectral method.Simulation experiments were carried out under three different types of obstacle environments and one multiobstacle environment,and the simulation results show that the method proposed in this paper greatly improves the success rate of UAV evasive maneuvers,proving the effectiveness of this method.
文摘The Titanic sunk 113 years ago on April 14-15,after hitting an iceberg,with human error likely causing the ship to wander into those dangerous waters.Today,autonomous systems built on AI can help ships avoid such accidents.But could such a system explain to the captain why it was controlling the ship in a certain way?
基金the Technology Project Managed by the State Grid Corporation of China(No.5108-202218280A-2-249-XG)。
文摘Mobile robots represented by smart wheelchairs can assist elderly people with mobility difficulties.This paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior maps.In order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic goals.At last,comparative experiments were carried out in the real environment.Results show that our method is superior in terms of safety,comfort and docking accuracy.
基金Supported by the National Natural Science Foundation of China(No.61971162,61771186)the Natural Science Foundation of Heilongjiang Province(No.PL2024F025)+1 种基金the Open Research Fund of National Mobile Communications Research Laboratory in Southeast University(No.2023D07)the Fundamental Scientific Research Funds of Heilongjiang Province(No.2022-KYYWF-1050).
文摘The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor environments and radio signal interference caused by multiwall environments,which collectively lead to significant positioning errors,vision-based positioning has emerged as a crucial method in indoor positioning research.This paper introduces a scale hierarchical matching model to tackle challenges associated with large visual databases and high scene similarity,both of which will compromise matching accuracy and lead to prolonged positioning delays.The proposed model establishes an image feature database using GIST features and speeded up robust feature(SURF)in the offline stage.In the online stage,a positioning navigating algorithm is constructed based on Dijkstra’s path planning.Additionally,a corresponding Android application has been developed to facilitate visual positioning and navigation in indoor environments.Experimental results obtained in real indoor environments demonstrate that the proposed method significantly enhances positioning accuracy compared with similar algorithms,while effectively reducing time overhead.This improvement caters to the requirements for indoor positioning and navigation,thereby meeting user needs.
