Under ongoing global warming,reliable projections of Arctic sea-ice conditions and future navigability are of strategic significance.Using a combination of observational and physical constraints,we systematically eval...Under ongoing global warming,reliable projections of Arctic sea-ice conditions and future navigability are of strategic significance.Using a combination of observational and physical constraints,we systematically evaluated the performance of 48 Coupled Model Intercomparison Project 6(CMIP6)models in simulating Arctic sea ice and selected 12 skillful models for detailed analysis.Navigability of the Northeast Passage(NEP),Northwest Passage(NWP),and Transpolar Sea Route(TSR)during 2015–2100 was assessed under Shared Socioeconomic Pathways(SSP)2-4.5 and SSP5-8.5 scenarios.Results indicate that for open water vessels under the SSP2-4.5,TSR is not projected to become navigable until 2029.In contrast,under the SSP5-8.5 scenario,both NWP and NEP are expected to support year-round navigation by the late 21st century,while TSR is not anticipated to become fully operational until after 2090.Polar Class 6 vessels achieve near year-round navigation by 2100 under SSP2-4.5,and full-year operation as early as 2048 under SSP5-8.5.展开更多
The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a ri...The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a risk of spoofing attacks.To improve the anti-spoofing capability of the SBAS,European Union and the United States conduct research on navigation message authentication,and promote the standardization of SBAS message authentication.For the development of Beidou satellite-based augmentation system(BDSBAS),this paper proposes navigation message authentication based on the Chinese commercial cryptographic standards.Firstly,this paper expounds the architecture and principles of the SBAS message authentication,and then carries out the design of timed efficient streaming losstolerant authentication scheme(TESLA)and elliptic curve digital signature algorithm(ECDSA)authentication schemes based on Chinese commercial cryptographic standards,message arrangement and the design of over-the-air rekeying(OTAR)message.Finally,this paper conducts a theoretical analysis of the time between authentications(TBA)and maximum authentication latency(MAL)for L5 TESLA-I and L5 ECDSA-Q,and further simulates the reception time of OTAR message,TBA and MAL from the aspects of OTAR message weight and demodulation error rate.The simulation results can provide theoretical supports for the standardization of BDSBAS message authentication.展开更多
Surgical navigation has evolved significantly through advances in augmented reality,virtual reality,and mixed reality,improving precision and safety across many clinical applications,including neurosurgery,maxillofaci...Surgical navigation has evolved significantly through advances in augmented reality,virtual reality,and mixed reality,improving precision and safety across many clinical applications,including neurosurgery,maxillofacial,spinal,and arthroplasty procedures.By integrating preoperative imaging with real-time intraoperative data,these systems provide dynamic guidance,reduce radiation exposure,and minimize tissue damage.Key challenges persist,including intraoperative registration accuracy,flexible tissue deformation,respiratory compensation,and real-time imaging quality.Emerging solutions include artificial intelligence-driven segmentation,deformation-field modeling,and hybrid registration techniques.Future developments will include lightweight,portable systems,improved non-rigid registration algorithms,and greater clinical adoption.Despite advances in rigid-tissue applications,soft-tissue navigation requires additional innovation to address motion variability and registration reliability,ultimately advancing minimally invasive surgery and precision medicine.展开更多
The current inertial measurement unit(IMU)and odometry fusion navigation algorithms often incorporate non-holonomic constraints(NHC)to obtain three-dimensional velocity in the navigation frame.However,due to the integ...The current inertial measurement unit(IMU)and odometry fusion navigation algorithms often incorporate non-holonomic constraints(NHC)to obtain three-dimensional velocity in the navigation frame.However,due to the integral nature of the dead reckoning algorithm,the attitude errors of the IMU accumulate over time,causing the velocity transformation results to fail to accurately reflect the threedimensional velocity in the navigation frame.Based on the fact that during a vehicle's horizontal and uniform motion,the vertical acceleration is consistent with gravitational acceleration,this paper proposes an IMU/odometry fusion navigation algorithm based on horizontal attitude constraints(HAC).Building on non-holonomic constraints,this algorithm determines the motion state of the vehicle through accelerometer output and zeroes out the pitch and roll angles during horizontal and uniform motion.Verified through two sets of real-world vehicle test data,this algorithm improves horizontal positioning accuracy by approximately 63%and 70%,and vertical positioning accuracy by 98%and 97%,compared with the traditional NHC IMU/odometer fusion algorithm.展开更多
Continuous and highly accurate navigation of long-endurance flight vehicles continues to be a substantial challenge in Global Navigation Satellite Systems(GNSS)-denied environments.Though the integrated navigation bas...Continuous and highly accurate navigation of long-endurance flight vehicles continues to be a substantial challenge in Global Navigation Satellite Systems(GNSS)-denied environments.Though the integrated navigation based on multiple sensors is used to improve the navigation performance,the existing methods are prone to model mismatch and error accumulation under heterogeneous conditions of sensors.In this paper,a Tightly-coupled Interactive Multi-Model Factor Graph Optimization(TIMMFGO) navigation method is proposed to solve the problem.The developed integrated navigation framework consists of Inertial Navigation Systems(INS),Celestial Navigation Systems(CNS),Radio Navigation Systems(RNS),and Barometric Altimeters(BA).We propose a CNS/INS tightly-coupled graph architecture that integrates star vector observations with INS pre-integration,enabling dynamic compensation of gyroscopic bias while correcting the attitude update accuracy of INS.Then,an Interactive Multi-Model(IMM) adaptive weighting strategy is used to combine the vertical RNS factor with the BA factor for position,which can effectively reduce the altitude bias induced by the spatial configuration constraints of RNS.The simulation demonstrates that compared to the Huber M-estimation-based FGO(HMFGO),Windowing Anomaly-Detection-based FGO(WADFGO) and IMM Unscented Kalman Filter(IMMUKF)methods,the TIMMFGO method improves attitude accuracy by 46.49 %,25.68 % and 20.67 %,respectively,while correspondingly reducing position accuracy by 29.29 %,10.79 % and 6.96 %.展开更多
With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Lap...With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery(LECSSNNS)has drawn increasing interest because of its dual benefits of minimal invasiveness and organ function preservation.However,robust evidence-based support for guiding clinical implementation remains limited.To address this gap,we systematically evaluated available studies on the clinical application of LECS-SNNS in EGC and integrated expert insights to formulate 20 recommendations.These included preoperative assessment,surgical techniques,intraoperative endoscopic procedures,pathological evaluation,postoperative care,and follow-up.This consensus aimed to provide comprehensive guidance for the standardized application of LECS-SNNS,thereby advancing precise,minimally invasive,and function-preserving treatment for EGC.展开更多
Unmanned Aerial Vehicle(UAV)plays a prominent role in various fields,and autonomous navigation is a crucial component of UAV intelligence.Deep Reinforcement Learning(DRL)has expanded the research avenues for addressin...Unmanned Aerial Vehicle(UAV)plays a prominent role in various fields,and autonomous navigation is a crucial component of UAV intelligence.Deep Reinforcement Learning(DRL)has expanded the research avenues for addressing challenges in autonomous navigation.Nonetheless,challenges persist,including getting stuck in local optima,consuming excessive computations during action space exploration,and neglecting deterministic experience.This paper proposes a noise-driven enhancement strategy.In accordance with the overall learning phases,a global noise control method is designed,while a differentiated local noise control method is developed by analyzing the exploration demands of four typical situations encountered by UAV during navigation.Both methods are integrated into a dual-model for noise control to regulate action space exploration.Furthermore,noise dual experience replay buffers are designed to optimize the rational utilization of both deterministic and noisy experience.In uncertain environments,based on the Twin Delay Deep Deterministic Policy Gradient(TD3)algorithm with Long Short-Term Memory(LSTM)network and Priority Experience Replay(PER),a Noise-Driven Enhancement Priority Memory TD3(NDE-PMTD3)is developed.We established a simulation environment to compare different algorithms,and the performance of the algorithms is analyzed in various scenarios.The training results indicate that the proposed algorithm accelerates the convergence speed and enhances the convergence stability.In test experiments,the proposed algorithm successfully and efficiently performs autonomous navigation tasks in diverse environments,demonstrating superior generalization results.展开更多
The decreasing of Arctic sea ice is projected to continue with global warming,which makes the summer navigation conditions of the Arctic improve.Based on the multi-source remote-sensing data with inter-sensor calibrat...The decreasing of Arctic sea ice is projected to continue with global warming,which makes the summer navigation conditions of the Arctic improve.Based on the multi-source remote-sensing data with inter-sensor calibration processing and the ship-based observational data from R/V Xuelong and M/V Yongsheng,the sea ice conditions of the Arctic Northeast Passage(NEP)during the 2002-2021 summer seasons were analyzed,and the navigability of the NEP between July and October from 2002 to 2021 was discussed.Inter-sensor calibration could effectively reduce the deviation from different passive microwave data.Sea ice extent and thickness in the NEP decreased annually,which resulted in the navigability of the NEP showing a potential tendency toward improvement in navigability.The navigation period was mainly concentrated in early August to early October.The middle part of the NEP was primarily affected by sea ice.This influence decreased over time,while the navigation period increased,especially in the Vilkitsky Strait,which is a key shipping area.This analysis of sea ice conditions and navigability in the past 20 years could provide a reference for future scientific investigations and aid in merchant ship navigation in the Arctic summer.展开更多
Purpose： This study introduces an algorithm to construct tag trees that can be used as a userfriendly navigation tool for knowledge sharing and retrieval by solving two issues of previous studies, i.e. semantic drift...Purpose： This study introduces an algorithm to construct tag trees that can be used as a userfriendly navigation tool for knowledge sharing and retrieval by solving two issues of previous studies, i.e. semantic drift and structural skew.Design/methodology/approach： Inspired by the generality based methods, this study builds tag trees from a co-occurrence tag network and uses the h-degree as a node generality metric. The proposed algorithm is characterized by the following four features：（1） the ancestors should be more representative than the descendants,（2） the semantic meaning along the ancestor-descendant paths needs to be coherent,（3） the children of one parent are collectively exhaustive and mutually exclusive in describing their parent, and（4） tags are roughly evenly distributed to their upper-level parents to avoid structural skew. Findings： The proposed algorithm has been compared with a well-established solution Heymann Tag Tree（HTT）. The experimental results using a social tag dataset showed that the proposed algorithm with its default condition outperformed HTT in precision based on Open Directory Project（ODP） classification. It has been verified that h-degree can be applied as a better node generality metric compared with degree centrality.Research limitations： A thorough investigation into the evaluation methodology is needed, including user studies and a set of metrics for evaluating semantic coherence and navigation performance.Practical implications： The algorithm will benefit the use of digital resources by generating a flexible domain knowledge structure that is easy to navigate. It could be used to manage multiple resource collections even without social annotations since tags can be keywords created by authors or experts, as well as automatically extracted from text.Originality/value： Few previous studies paid attention to the issue of whether the tagging systems are easy to navigate for users. The contributions of this study are twofold：（1） an algorithm was developed to construct tag trees with consideration given to both semanticcoherence and structural balance and（2） the effectiveness of a node generality metric, h-degree, was investigated in a tag co-occurrence network.展开更多
Direction navigability analysis is a supplement to the navigability analysis theory, in which extraction of the direction suitable-matching features(DSMFs) determines the evaluation performance. A method based on the ...Direction navigability analysis is a supplement to the navigability analysis theory, in which extraction of the direction suitable-matching features(DSMFs) determines the evaluation performance. A method based on the Gabor filter is proposed to estimate the direction navigability of the geomagnetic field. First,the DSMFs are extracted based on the Gabor filter’s responses.Second, in the view of pattern recognition, the classification accuracy in fault diagnosis is introduced as the objective function of the hybrid particle swarm optimization(HPSO) algorithm to optimize the Gabor filter’s parameters. With its guidance, the DSMFs are extracted. Finally, a direction navigability analysis model is established with the support vector machine(SVM), and the performances of the models under different objective functions are discussed. Simulation results show the parameters of the Gabor filter have a significant influence on the DSMFs, which, in turn, affects the analysis results of direction navigability. Moreover, the risk of misclassification can be effectively reduced by using the analysis model with optimal Gabor filter parameters. The proposed method is not restricted in geomagnetic navigation, and it also can be used in other fields such as terrain matching and gravity 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
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
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
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
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
基金supported by the National Natural Science Foundation of China(Grant no.42430411)the National Key Research and Development Program of China(Grant no.2019YFA0607004)+1 种基金the National Natural Science Foundation of China(Grant no.42075024)the Innovation and Development Program of China Meteorological Administration(Grant no.CXFZ2024J033).
文摘Under ongoing global warming,reliable projections of Arctic sea-ice conditions and future navigability are of strategic significance.Using a combination of observational and physical constraints,we systematically evaluated the performance of 48 Coupled Model Intercomparison Project 6(CMIP6)models in simulating Arctic sea ice and selected 12 skillful models for detailed analysis.Navigability of the Northeast Passage(NEP),Northwest Passage(NWP),and Transpolar Sea Route(TSR)during 2015–2100 was assessed under Shared Socioeconomic Pathways(SSP)2-4.5 and SSP5-8.5 scenarios.Results indicate that for open water vessels under the SSP2-4.5,TSR is not projected to become navigable until 2029.In contrast,under the SSP5-8.5 scenario,both NWP and NEP are expected to support year-round navigation by the late 21st century,while TSR is not anticipated to become fully operational until after 2090.Polar Class 6 vessels achieve near year-round navigation by 2100 under SSP2-4.5,and full-year operation as early as 2048 under SSP5-8.5.
基金supported by National Natural Science Foundation of China:Space-based occultation detection with ground-based GNSS atmospheric horizontal gradient model(41904033).
文摘The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a risk of spoofing attacks.To improve the anti-spoofing capability of the SBAS,European Union and the United States conduct research on navigation message authentication,and promote the standardization of SBAS message authentication.For the development of Beidou satellite-based augmentation system(BDSBAS),this paper proposes navigation message authentication based on the Chinese commercial cryptographic standards.Firstly,this paper expounds the architecture and principles of the SBAS message authentication,and then carries out the design of timed efficient streaming losstolerant authentication scheme(TESLA)and elliptic curve digital signature algorithm(ECDSA)authentication schemes based on Chinese commercial cryptographic standards,message arrangement and the design of over-the-air rekeying(OTAR)message.Finally,this paper conducts a theoretical analysis of the time between authentications(TBA)and maximum authentication latency(MAL)for L5 TESLA-I and L5 ECDSA-Q,and further simulates the reception time of OTAR message,TBA and MAL from the aspects of OTAR message weight and demodulation error rate.The simulation results can provide theoretical supports for the standardization of BDSBAS message authentication.
基金Supported by the National Natural Science Foundation of China(NSFC)under Grants 62025104,62422102,62331005,62301034,and U22A2052the Beijing Natural Science Foundation-Daxing Innovation Joint Fund(L256040).
文摘Surgical navigation has evolved significantly through advances in augmented reality,virtual reality,and mixed reality,improving precision and safety across many clinical applications,including neurosurgery,maxillofacial,spinal,and arthroplasty procedures.By integrating preoperative imaging with real-time intraoperative data,these systems provide dynamic guidance,reduce radiation exposure,and minimize tissue damage.Key challenges persist,including intraoperative registration accuracy,flexible tissue deformation,respiratory compensation,and real-time imaging quality.Emerging solutions include artificial intelligence-driven segmentation,deformation-field modeling,and hybrid registration techniques.Future developments will include lightweight,portable systems,improved non-rigid registration algorithms,and greater clinical adoption.Despite advances in rigid-tissue applications,soft-tissue navigation requires additional innovation to address motion variability and registration reliability,ultimately advancing minimally invasive surgery and precision medicine.
基金from the National Key Research and Development Program project"Adaptive Navigation Software and Hardware Technology(2018YFB0505200)."。
文摘The current inertial measurement unit(IMU)and odometry fusion navigation algorithms often incorporate non-holonomic constraints(NHC)to obtain three-dimensional velocity in the navigation frame.However,due to the integral nature of the dead reckoning algorithm,the attitude errors of the IMU accumulate over time,causing the velocity transformation results to fail to accurately reflect the threedimensional velocity in the navigation frame.Based on the fact that during a vehicle's horizontal and uniform motion,the vertical acceleration is consistent with gravitational acceleration,this paper proposes an IMU/odometry fusion navigation algorithm based on horizontal attitude constraints(HAC).Building on non-holonomic constraints,this algorithm determines the motion state of the vehicle through accelerometer output and zeroes out the pitch and roll angles during horizontal and uniform motion.Verified through two sets of real-world vehicle test data,this algorithm improves horizontal positioning accuracy by approximately 63%and 70%,and vertical positioning accuracy by 98%and 97%,compared with the traditional NHC IMU/odometer fusion algorithm.
基金co-supported by the Open Fund of National Natural Science Foundation of China(No.62401042)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(No.2023QNRC001)。
文摘Continuous and highly accurate navigation of long-endurance flight vehicles continues to be a substantial challenge in Global Navigation Satellite Systems(GNSS)-denied environments.Though the integrated navigation based on multiple sensors is used to improve the navigation performance,the existing methods are prone to model mismatch and error accumulation under heterogeneous conditions of sensors.In this paper,a Tightly-coupled Interactive Multi-Model Factor Graph Optimization(TIMMFGO) navigation method is proposed to solve the problem.The developed integrated navigation framework consists of Inertial Navigation Systems(INS),Celestial Navigation Systems(CNS),Radio Navigation Systems(RNS),and Barometric Altimeters(BA).We propose a CNS/INS tightly-coupled graph architecture that integrates star vector observations with INS pre-integration,enabling dynamic compensation of gyroscopic bias while correcting the attitude update accuracy of INS.Then,an Interactive Multi-Model(IMM) adaptive weighting strategy is used to combine the vertical RNS factor with the BA factor for position,which can effectively reduce the altitude bias induced by the spatial configuration constraints of RNS.The simulation demonstrates that compared to the Huber M-estimation-based FGO(HMFGO),Windowing Anomaly-Detection-based FGO(WADFGO) and IMM Unscented Kalman Filter(IMMUKF)methods,the TIMMFGO method improves attitude accuracy by 46.49 %,25.68 % and 20.67 %,respectively,while correspondingly reducing position accuracy by 29.29 %,10.79 % and 6.96 %.
基金supported by National Key Research and Development Program of China(No.2023YFC2507406)National Natural Science Foundation of China(No.82300646)+6 种基金Beijing Natural Science Foundation(No.7232334)Beijing Municipal Administration of Hospitals Incubating Program(No.PX2024002,PX2020001)Capital Fund for Health Development Scientific Research(No.2024-2-2028)Beijing Municipal Science&Technology Commission AI+Health Collaborative Innovation Cultivation Project(No.Z241100007724004)Research Ward Excellence Program of Beijing Municipal Health Commission(No.BRWEP2024W162020100,BRWEP2024W162020112,BRWEP2024W162020114)Excellent Plan for Capital Medicine Scientific and Technological Innovation Achievement Transformation Promotion Plan(No.YC202401QX0824)Clinical Scientific Research Fund of Beijing Integrated Medical Association[No.ZHKY-2025-1869(B012)]。
文摘With the advancement of surgical techniques and enhanced management of early gastric cancer(EGC),minimally invasive function-preserving surgical approaches have emerged as a common goal for patients and clinicians.Laparoscopic-endoscopic cooperative surgery combined with sentinel lymph node navigation surgery(LECSSNNS)has drawn increasing interest because of its dual benefits of minimal invasiveness and organ function preservation.However,robust evidence-based support for guiding clinical implementation remains limited.To address this gap,we systematically evaluated available studies on the clinical application of LECS-SNNS in EGC and integrated expert insights to formulate 20 recommendations.These included preoperative assessment,surgical techniques,intraoperative endoscopic procedures,pathological evaluation,postoperative care,and follow-up.This consensus aimed to provide comprehensive guidance for the standardized application of LECS-SNNS,thereby advancing precise,minimally invasive,and function-preserving treatment for EGC.
基金the Collaborative Innovation Project of Shanghai,China for the financial support。
文摘Unmanned Aerial Vehicle(UAV)plays a prominent role in various fields,and autonomous navigation is a crucial component of UAV intelligence.Deep Reinforcement Learning(DRL)has expanded the research avenues for addressing challenges in autonomous navigation.Nonetheless,challenges persist,including getting stuck in local optima,consuming excessive computations during action space exploration,and neglecting deterministic experience.This paper proposes a noise-driven enhancement strategy.In accordance with the overall learning phases,a global noise control method is designed,while a differentiated local noise control method is developed by analyzing the exploration demands of four typical situations encountered by UAV during navigation.Both methods are integrated into a dual-model for noise control to regulate action space exploration.Furthermore,noise dual experience replay buffers are designed to optimize the rational utilization of both deterministic and noisy experience.In uncertain environments,based on the Twin Delay Deep Deterministic Policy Gradient(TD3)algorithm with Long Short-Term Memory(LSTM)network and Priority Experience Replay(PER),a Noise-Driven Enhancement Priority Memory TD3(NDE-PMTD3)is developed.We established a simulation environment to compare different algorithms,and the performance of the algorithms is analyzed in various scenarios.The training results indicate that the proposed algorithm accelerates the convergence speed and enhances the convergence stability.In test experiments,the proposed algorithm successfully and efficiently performs autonomous navigation tasks in diverse environments,demonstrating superior generalization results.
基金supported by the National Key Research and Development Program of China[grant number 2017YFA0603104]the National Natural Science Foundation of China[grant number 42076235]+1 种基金the Fundamental Research Funds for the Central Universities[grant number 2042022kf0018]the Special Fund for High Resolution Images Surveying and Mapping Application[grant number 42-Y30B04-9001-19/21]。
文摘The decreasing of Arctic sea ice is projected to continue with global warming,which makes the summer navigation conditions of the Arctic improve.Based on the multi-source remote-sensing data with inter-sensor calibration processing and the ship-based observational data from R/V Xuelong and M/V Yongsheng,the sea ice conditions of the Arctic Northeast Passage(NEP)during the 2002-2021 summer seasons were analyzed,and the navigability of the NEP between July and October from 2002 to 2021 was discussed.Inter-sensor calibration could effectively reduce the deviation from different passive microwave data.Sea ice extent and thickness in the NEP decreased annually,which resulted in the navigability of the NEP showing a potential tendency toward improvement in navigability.The navigation period was mainly concentrated in early August to early October.The middle part of the NEP was primarily affected by sea ice.This influence decreased over time,while the navigation period increased,especially in the Vilkitsky Strait,which is a key shipping area.This analysis of sea ice conditions and navigability in the past 20 years could provide a reference for future scientific investigations and aid in merchant ship navigation in the Arctic summer.
基金funded by the National Natural Science Foundation of China(Grand No.:70903008)supported by COGS Lab in School of Government,Beijing Normal University
文摘Purpose： This study introduces an algorithm to construct tag trees that can be used as a userfriendly navigation tool for knowledge sharing and retrieval by solving two issues of previous studies, i.e. semantic drift and structural skew.Design/methodology/approach： Inspired by the generality based methods, this study builds tag trees from a co-occurrence tag network and uses the h-degree as a node generality metric. The proposed algorithm is characterized by the following four features：（1） the ancestors should be more representative than the descendants,（2） the semantic meaning along the ancestor-descendant paths needs to be coherent,（3） the children of one parent are collectively exhaustive and mutually exclusive in describing their parent, and（4） tags are roughly evenly distributed to their upper-level parents to avoid structural skew. Findings： The proposed algorithm has been compared with a well-established solution Heymann Tag Tree（HTT）. The experimental results using a social tag dataset showed that the proposed algorithm with its default condition outperformed HTT in precision based on Open Directory Project（ODP） classification. It has been verified that h-degree can be applied as a better node generality metric compared with degree centrality.Research limitations： A thorough investigation into the evaluation methodology is needed, including user studies and a set of metrics for evaluating semantic coherence and navigation performance.Practical implications： The algorithm will benefit the use of digital resources by generating a flexible domain knowledge structure that is easy to navigate. It could be used to manage multiple resource collections even without social annotations since tags can be keywords created by authors or experts, as well as automatically extracted from text.Originality/value： Few previous studies paid attention to the issue of whether the tagging systems are easy to navigate for users. The contributions of this study are twofold：（1） an algorithm was developed to construct tag trees with consideration given to both semanticcoherence and structural balance and（2） the effectiveness of a node generality metric, h-degree, was investigated in a tag co-occurrence network.
基金supported by the Key Project of Military Research on Weapons and Equipment(2014551)
文摘Direction navigability analysis is a supplement to the navigability analysis theory, in which extraction of the direction suitable-matching features(DSMFs) determines the evaluation performance. A method based on the Gabor filter is proposed to estimate the direction navigability of the geomagnetic field. First,the DSMFs are extracted based on the Gabor filter’s responses.Second, in the view of pattern recognition, the classification accuracy in fault diagnosis is introduced as the objective function of the hybrid particle swarm optimization(HPSO) algorithm to optimize the Gabor filter’s parameters. With its guidance, the DSMFs are extracted. Finally, a direction navigability analysis model is established with the support vector machine(SVM), and the performances of the models under different objective functions are discussed. Simulation results show the parameters of the Gabor filter have a significant influence on the DSMFs, which, in turn, affects the analysis results of direction navigability. Moreover, the risk of misclassification can be effectively reduced by using the analysis model with optimal Gabor filter parameters. The proposed method is not restricted in geomagnetic navigation, and it also can be used in other fields such as terrain matching and gravity 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.
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 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.
