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
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
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
Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecis...Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecision ZTD model.However,existing ZTD models only consider the impact of linear terms on ZTD estimation,whereas the nonlinear factors have rarely been investigated before and thus become the focus of this study.A real-time and high-precision ZTD model for large height difference area is proposed by considering the linear and nonlinear characteristics of ZTD spatiotemporal variations and is called the realtime linear and nonlinearity ZTD(RLNZ)model.This model uses the ZTD estimated from the Global Pressure and Temperature 3(GPT3)model as the initial value.The linear impacts of periodic term and height on the estimation of ZTD difference between GNSS and GPT3 model are first considered.In addition,nonlinear factors such as geographical location and time are further used to fit the remaining nonlinear ZTD residuals using the general regression neural network method.Finally,the RLNZ-derived ZTD is obtained at an arbitrary location.The western United States,with height difference ranging from-500 to 4000 m,is selected,and the hourly ZTD of 484 GNSS stations provided by the Nevada Geodetic Laboratory(NGL)and the data of 9 radiosonde(RS)stations in the year 2021 are used.Experiment results show that a better performance of ZTD estimation can be retrieved from the proposed RLNZ model when compared with the GPT3 model.Statistical results show the averaged root mean square(RMS),Bias,and mean absolute error(MAE)of ZTD from GPT3 and RLNZ models are 33.7/0.8/25.7 mm and 22.6/0.1/17.4 mm,respectively.The average improvement rate of the RLNZ model is 33% when compared to the GPT3 model.Finally,the application of the proposed RLNZ model in simulated real-time Precise Point Positioning(PPP)indicates that the accuracy of PPP in N,E and U components is improved by 8%,2%,and 6% when compared with that from the GPT3-based PPP.Meanwhile,the convergence time in N and U components is improved by 23% and 7%,respectively.Such results verify the superiority of the proposed RLNZ model in retrieving realtime ZTD maps for GNSS positioning and navigation applications.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
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
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
Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial...Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.展开更多
Large-aperture optical components are of paramount importance in domains such as integrated circuits,photolithography,aerospace,and inertial confinement fusion.However,measuring their surface profiles relies predomina...Large-aperture optical components are of paramount importance in domains such as integrated circuits,photolithography,aerospace,and inertial confinement fusion.However,measuring their surface profiles relies predominantly on the phase-shifting approach,which involves collecting multiple interferograms and imposes stringent demands on environmental stability.These issues significantly hinder its ability to achieve real-time and dynamic high-precision measurements.Therefore,this study proposes a high-precision large-aperture single-frame interferometric surface profile measurement(LA-SFISPM)method based on deep learning and explores its capability to realize dynamic measurements with high accuracy.The interferogram is matched to the phase by training the data measured using the small aperture.The consistency of the surface features of the small and large apertures is enhanced via contrast learning and feature-distribution alignment.Hence,high-precision phase reconstruction of large-aperture optical components can be achieved without using a phase shifter.The experimental results show that for the tested mirror withΦ=820 mm,the surface profile obtained from LA-SFISPM is subtracted point-by-point from the ground truth,resulting in a maximum single-point error of 4.56 nm.Meanwhile,the peak-to-valley(PV)value is 0.0758λ,and the simple repeatability of root mean square(SR-RMS)value is 0.00025λ,which aligns well with the measured results obtained by ZYGO.In particular,a significant reduction in the measurement time(reduced by a factor of 48)is achieved compared with that of the traditional phase-shifting method.Our proposed method provides an efficient,rapid,and accurate method for obtaining the surface profiles of optical components with different diameters without employing a phase-shifting approach,which is highly desired in large-aperture interferometric measurement systems.展开更多
Since the Carter administration launched the“Freedom of Navigation Program”(FON Program)in 1979,the United States has been conducting“Freedom of Navigation Operations”(FONOPs)and frequently dispatching warships an...Since the Carter administration launched the“Freedom of Navigation Program”(FON Program)in 1979,the United States has been conducting“Freedom of Navigation Operations”(FONOPs)and frequently dispatching warships and military aircraft into waters under the jurisdiction of other coastal States to challenge the so-called“excessive maritime claims.”1 According to official statistics from the US Department of Defense,during fiscal year 2023 alone,the US FONOPs challenged 29“excessive maritime claims”by 17 coastal States,an increase from the 22“excessive maritime claims”by 15 coastal States challenged in FY2022.2 The US“freedom of navigation”frequently causes unnecessary frictions.In several severe cases,it leads to maritime and aerial accidents.展开更多
The elliptic integral method(EIM) is an efficient analytical approach for analyzing large deformations of elastic beams. However, it faces the following challenges.First, the existing EIM can only handle cases with kn...The elliptic integral method(EIM) is an efficient analytical approach for analyzing large deformations of elastic beams. However, it faces the following challenges.First, the existing EIM can only handle cases with known deformation modes. Second,the existing EIM is only applicable to Euler beams, and there is no EIM available for higher-precision Timoshenko and Reissner beams in cases where both force and moment are applied at the end. This paper proposes a general EIM for Reissner beams under arbitrary boundary conditions. On this basis, an analytical equation for determining the sign of the elliptic integral is provided. Based on the equation, we discover a class of elliptic integral piecewise points that are distinct from inflection points. More importantly, we propose an algorithm that automatically calculates the number of inflection points and other piecewise points during the nonlinear solution process, which is crucial for beams with unknown or changing deformation modes.展开更多
Micro/nanorobots have significant potential applications in biomedicine.However,their small size and the need for intricate control make long-distance navigation of microswarms composed of such robots challenging in c...Micro/nanorobots have significant potential applications in biomedicine.However,their small size and the need for intricate control make long-distance navigation of microswarms composed of such robots challenging in complex environments.To address this problem,we have developed a permanent-magnet-actuated microswarm navigation system to achieve precise control of micro/nanorobots in complex fluid environments.The controlled microswarm is composed of monodisperse Fe_(3)O_(4)@PVP nanoclusters synthesized using the polyol method.These nanoclusters can self-assemble into highly controllable microswarm structures under a rotating magnetic field and are then guided by the robotic system for precise navigation.The system uses visual positioning and motion control to enable real-time dynamic navigation.In experiments,it successfully performed autonomous navigation over a 55 mm distance in a transparent channel,with flow rates ranging from 0 to 10 mm/s.It completed the task in 132 s at an average speed of over 0.45 mm/s,with an average trajectory tracking error of only 0.28 mm.These results demonstrate excellent path accuracy and stability under various flow rate conditions,validating the system’s adaptability and efficiency in fluid environments and highlighting its potential for biomedical applications.This study offers a robust and versatile platform for expanding micro/nanorobot applications in biomedicine.展开更多
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.
基金supported by the National Natural Science Foundation of China(42274039)Shaanxi Provincial Innovation Capacity Support Plan Project(2023KJXX-050)+2 种基金The Open Grants of the State Key Laboratory of Severe Weather(2023LASW-B18)Scientific and technological research projects for major issues in military medicine and aviation medicine(2022ZZXM012)Local special scientific research plan project of Shaanxi Provincial Department of Education(22JE012)。
文摘Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecision ZTD model.However,existing ZTD models only consider the impact of linear terms on ZTD estimation,whereas the nonlinear factors have rarely been investigated before and thus become the focus of this study.A real-time and high-precision ZTD model for large height difference area is proposed by considering the linear and nonlinear characteristics of ZTD spatiotemporal variations and is called the realtime linear and nonlinearity ZTD(RLNZ)model.This model uses the ZTD estimated from the Global Pressure and Temperature 3(GPT3)model as the initial value.The linear impacts of periodic term and height on the estimation of ZTD difference between GNSS and GPT3 model are first considered.In addition,nonlinear factors such as geographical location and time are further used to fit the remaining nonlinear ZTD residuals using the general regression neural network method.Finally,the RLNZ-derived ZTD is obtained at an arbitrary location.The western United States,with height difference ranging from-500 to 4000 m,is selected,and the hourly ZTD of 484 GNSS stations provided by the Nevada Geodetic Laboratory(NGL)and the data of 9 radiosonde(RS)stations in the year 2021 are used.Experiment results show that a better performance of ZTD estimation can be retrieved from the proposed RLNZ model when compared with the GPT3 model.Statistical results show the averaged root mean square(RMS),Bias,and mean absolute error(MAE)of ZTD from GPT3 and RLNZ models are 33.7/0.8/25.7 mm and 22.6/0.1/17.4 mm,respectively.The average improvement rate of the RLNZ model is 33% when compared to the GPT3 model.Finally,the application of the proposed RLNZ model in simulated real-time Precise Point Positioning(PPP)indicates that the accuracy of PPP in N,E and U components is improved by 8%,2%,and 6% when compared with that from the GPT3-based PPP.Meanwhile,the convergence time in N and U components is improved by 23% and 7%,respectively.Such results verify the superiority of the proposed RLNZ model in retrieving realtime ZTD maps for GNSS positioning and navigation applications.
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.
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.
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.
基金supported by the projects funded by the Education Department of Shaanxi Provincial Government(NO.23JP116)the Natural Science Fund of Shaanxi Province(NO.2024JC-YBMS-396)+3 种基金the National Natural Science Foundation of China(NO.52171191,52371198,U22A20137)the Constructing National Independent Innovation Demonstration Zones(XM2024XTGXQ05)Shenzhen Science and Technology Innovation Program(JCYJ20220818102215033,GJHZ20210705142542015,JCYJ20220530160811027)Guangdong HUST Industrial Technology Research Institute,Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization(2023B1212060012).
文摘Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.
基金funded by the National Natural Science Foundation of China Instrumentation Program(52327806)Youth Fund of the National Nature Foundation of China(62405020)China Postdoctoral Science Foundation(2024M764131).
文摘Large-aperture optical components are of paramount importance in domains such as integrated circuits,photolithography,aerospace,and inertial confinement fusion.However,measuring their surface profiles relies predominantly on the phase-shifting approach,which involves collecting multiple interferograms and imposes stringent demands on environmental stability.These issues significantly hinder its ability to achieve real-time and dynamic high-precision measurements.Therefore,this study proposes a high-precision large-aperture single-frame interferometric surface profile measurement(LA-SFISPM)method based on deep learning and explores its capability to realize dynamic measurements with high accuracy.The interferogram is matched to the phase by training the data measured using the small aperture.The consistency of the surface features of the small and large apertures is enhanced via contrast learning and feature-distribution alignment.Hence,high-precision phase reconstruction of large-aperture optical components can be achieved without using a phase shifter.The experimental results show that for the tested mirror withΦ=820 mm,the surface profile obtained from LA-SFISPM is subtracted point-by-point from the ground truth,resulting in a maximum single-point error of 4.56 nm.Meanwhile,the peak-to-valley(PV)value is 0.0758λ,and the simple repeatability of root mean square(SR-RMS)value is 0.00025λ,which aligns well with the measured results obtained by ZYGO.In particular,a significant reduction in the measurement time(reduced by a factor of 48)is achieved compared with that of the traditional phase-shifting method.Our proposed method provides an efficient,rapid,and accurate method for obtaining the surface profiles of optical components with different diameters without employing a phase-shifting approach,which is highly desired in large-aperture interferometric measurement systems.
文摘Since the Carter administration launched the“Freedom of Navigation Program”(FON Program)in 1979,the United States has been conducting“Freedom of Navigation Operations”(FONOPs)and frequently dispatching warships and military aircraft into waters under the jurisdiction of other coastal States to challenge the so-called“excessive maritime claims.”1 According to official statistics from the US Department of Defense,during fiscal year 2023 alone,the US FONOPs challenged 29“excessive maritime claims”by 17 coastal States,an increase from the 22“excessive maritime claims”by 15 coastal States challenged in FY2022.2 The US“freedom of navigation”frequently causes unnecessary frictions.In several severe cases,it leads to maritime and aerial accidents.
基金supported by the National Natural Science Foundation of China (Nos. 12172388 and 12472400)the Guangdong Basic and Applied Basic Research Foundation of China(No. 2025A1515011975)the Scientific Research Project of Guangdong Polytechnic Normal University of China (No. 2023SDKYA010)
文摘The elliptic integral method(EIM) is an efficient analytical approach for analyzing large deformations of elastic beams. However, it faces the following challenges.First, the existing EIM can only handle cases with known deformation modes. Second,the existing EIM is only applicable to Euler beams, and there is no EIM available for higher-precision Timoshenko and Reissner beams in cases where both force and moment are applied at the end. This paper proposes a general EIM for Reissner beams under arbitrary boundary conditions. On this basis, an analytical equation for determining the sign of the elliptic integral is provided. Based on the equation, we discover a class of elliptic integral piecewise points that are distinct from inflection points. More importantly, we propose an algorithm that automatically calculates the number of inflection points and other piecewise points during the nonlinear solution process, which is crucial for beams with unknown or changing deformation modes.
基金supported by the National Natural Science Foundation of China(Grant No.52073222)the Fundamental Research Funds for the Central Universities(Grant No.WUT:104972024JYS0027).
文摘Micro/nanorobots have significant potential applications in biomedicine.However,their small size and the need for intricate control make long-distance navigation of microswarms composed of such robots challenging in complex environments.To address this problem,we have developed a permanent-magnet-actuated microswarm navigation system to achieve precise control of micro/nanorobots in complex fluid environments.The controlled microswarm is composed of monodisperse Fe_(3)O_(4)@PVP nanoclusters synthesized using the polyol method.These nanoclusters can self-assemble into highly controllable microswarm structures under a rotating magnetic field and are then guided by the robotic system for precise navigation.The system uses visual positioning and motion control to enable real-time dynamic navigation.In experiments,it successfully performed autonomous navigation over a 55 mm distance in a transparent channel,with flow rates ranging from 0 to 10 mm/s.It completed the task in 132 s at an average speed of over 0.45 mm/s,with an average trajectory tracking error of only 0.28 mm.These results demonstrate excellent path accuracy and stability under various flow rate conditions,validating the system’s adaptability and efficiency in fluid environments and highlighting its potential for biomedical applications.This study offers a robust and versatile platform for expanding micro/nanorobot applications in biomedicine.
