Lossy image coding is the art of computing that is principally bounded by the image’s rate-distortion function.This bound,though never accurately characterized,has been approached practically via deep learning techno...Lossy image coding is the art of computing that is principally bounded by the image’s rate-distortion function.This bound,though never accurately characterized,has been approached practically via deep learning technologies in recent years.Indeed,learned image coding schemes allow direct optimization of the joint rate-distortion cost,thereby outperforming the handcrafted image coding schemes by a large margin.Still,it is observed that there is room for further improvement in the rate-distortion performance of learned image coding.In this article,we identify the gap between the ideal rate-distortion function forecasted by Shannon’s information theory and the empirical rate-distortion function achieved by the state-of-the-art learned image coding schemes,revealing that the gap is incurred by five different effects:modeling effect,approximation effect,amortization effect,digitization effect,and asymptotic effect.We design simulations and experiments to quantitatively evaluate the last three effects,which demonstrates the high potential of future lossy image coding technologies.展开更多
This paper proposes a novel Range Migration Algorithm(RMA)integrated with an adaptive background filtering method specifically designed for near-field millimeter-wave imaging scenarios where targets are in close proxi...This paper proposes a novel Range Migration Algorithm(RMA)integrated with an adaptive background filtering method specifically designed for near-field millimeter-wave imaging scenarios where targets are in close proximity to background structures.This method simulates the attention distribution mode of the human visual system which is used in Artificial Intelligence(AI)and called the Attention Mechanism.Based on the concept of static clutter filtering,the frequency-domain signals of the scanning aperture are divided into grid cells.Background scattering functions are established by analyzing the motion processes within each cell,and the background interference is linearly filtered out.An analysis of the manifestation of background scattering interference within the algorithm is carried out,and the impact of the grid cell dimension on the imaging quality is investigated.Experimental results show that the proposed method exhibits the capability to enhance the signal-to-noise ratio of both the target and the background.It effectively suppresses the background interference,leading to a more prominent image,meanwhile without imposing the excessive computational load.The method offers a novel solution for improving the performance of millimeter-wave imaging technology in practical applications.展开更多
2025年12月22日,上海交通大学医学院医学技术学院李文杰在人工智能与信息融合领域国际顶级期刊Information Fusion发表了一项研究成果“CX-Mind:a pioneering multimodal large language model for interleaved reasoning in chest X-ra...2025年12月22日,上海交通大学医学院医学技术学院李文杰在人工智能与信息融合领域国际顶级期刊Information Fusion发表了一项研究成果“CX-Mind:a pioneering multimodal large language model for interleaved reasoning in chest X-ray via curriculum-guided reinforcement learning”。展开更多
为了保证运维阶段桥梁结构安全,提升桥梁运维工作的效率,开展公路混凝土梁式桥运维阶段建筑信息模型(building information modeling,BIM)技术应用研究。在对公路桥梁现行编码体系进行扩展的基础上,提出1种参数化快速建模方法,以快速完...为了保证运维阶段桥梁结构安全,提升桥梁运维工作的效率,开展公路混凝土梁式桥运维阶段建筑信息模型(building information modeling,BIM)技术应用研究。在对公路桥梁现行编码体系进行扩展的基础上,提出1种参数化快速建模方法,以快速完成桥梁构件族的创建与整体模型的集成。借助Autodesk Revit软件应用程序编程接口(application programming interface,API),采用C#语言,开发公路混凝土梁式桥智慧运维状态评估系统,以实际工程应用进行验证分析。研究结果表明:全面统一的桥梁信息编码体系,能够提高桥梁信息统计与检索效率;提出的快速建模方法能够显著减少建模工作量,建模时间较传统建模方法可减少60%,并保证模型的准确性与规范性;运维状态评估系统能够实现养护数据的充分利用与桥梁评定工作的自动化,通过对桥梁运维信息的有效组织,实现服役性能的长期追踪,从而确保运营期桥梁结构状态安全稳定。研究结果可为公路混凝土梁式桥运维管理提供技术支撑,提升桥梁运维的数字化水平。展开更多
Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable track...Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.展开更多
Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an inte...Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an integrated approach that combines a Three-Dimensional Finite-Time Optimal Cooperative Guidance Law(FTOC)with an Information Fusion Anti-saturation Predefined-time Observer(IFAPO).The proposed FTOC guidance law employs a nonlinear,non-quadratic finite-time optimal control strategy designed for rapid convergence within the limited timeframes of near-space interceptions,avoiding the need for remaining flight time estimation or linear decoupling inherent in traditional methods.To complement the guidance strategy,the IFAPO leverages multi-source information fusion theory and incorporates anti-saturation mechanisms to enhance target maneuver estimation.This method ensures accurate and real-time prediction of target acceleration while maintaining predefined convergence performance,even under complex interception conditions.By integrating the FTOC guidance law and IFAPO,the approach optimizes cooperative missile positioning,improves interception success rates,and minimizes fuel consumption,addressing practical constraints in military applications.Simulation results and comparative analyses confirm the effectiveness of the integrated approach,demonstrating its capability to achieve cooperative interception of highly maneuvering targets with enhanced efficiency and reduced economic costs,aligning with realistic combat scenarios.展开更多
High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelations...High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelationships among intricate variable patterns.Accordingly,this study proposes a Mogrifier gate recurrent unit-D(Mog-GRU-D)model to address the com-bat target intention prediction issue under the incomplete infor-mation condition.The proposed model directly processes miss-ing data while reducing the independence between inputs and output states.A total of 1200 samples from twelve continuous moments are captured through the combat simulation system,each of which consists of seven dimensional features.To bench-mark the experiment,a missing valued dataset has been gener-ated by randomly removing 20%of the original data.Extensive experiments demonstrate that the proposed model obtains the state-of-the-art performance with an accuracy of 73.25%when dealing with incomplete information.This study provides possi-ble interpretations for the principle of target interactive mecha-nism,highlighting the model’s effectiveness in potential air war-fare implementation.展开更多
Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the con...Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the context of fewshot and zero-shot scenarios remains highly challenging due to the scarcity of training data.Large language models(LLMs),on the other hand,can generalize well to unseen tasks with few-shot demonstrations or even zero-shot instructions and have demonstrated impressive ability for a wide range of natural language understanding or generation tasks.Nevertheless,it is unclear,whether such effectiveness can be replicated in the task of IE,where the target tasks involve specialized schema and quite abstractive entity or relation concepts.In this paper,we first examine the validity of LLMs in executing IE tasks with an established prompting strategy and further propose multiple types of augmented prompting methods,including the structured fundamental prompt(SFP),the structured interactive reasoning prompt(SIRP),and the voting-enabled structured interactive reasoning prompt(VESIRP).The experimental results demonstrate that while directly promotes inferior performance,the proposed augmented prompt methods significantly improve the extraction accuracy,achieving comparable or even better performance(e.g.,zero-shot FewNERD,FewNERD-INTRA)than state-of-theart methods that require large-scale training samples.This study represents a systematic exploration of employing instruction-following LLM for the task of IE.It not only establishes a performance benchmark for this novel paradigm but,more importantly,validates a practical technical pathway through the proposed prompt enhancement method,offering a viable solution for efficient IE in low-resource settings.展开更多
The transportation sector’s reliance on petroleum fuels exacerbates environmental issues,emphasizing the need for sustainable development.Online electric vehicle(EV)car-hailing services present a key opportunity for ...The transportation sector’s reliance on petroleum fuels exacerbates environmental issues,emphasizing the need for sustainable development.Online electric vehicle(EV)car-hailing services present a key opportunity for EV adoption.This study develops a model based on heuristic and systematic information processing,examining the impacts of factors such as perceived risk,information need,and experience and knowledge on users’utilization of online electric vehicle carhailing services.The results indicate that users’experience and knowledge increase their information need and promote both heuristic and systematic processing,leading to positive attitude change,although they don’t significantly affect perceived risk.Perceived risk increases information need and supports supports systematic processing but negatively impacts attitude change.Greater information enhances systematic processing and attitude change.Perceived risk and information need do not affect attitude change via heuristic processing.Finally,the paper concludes with implications and directions for future research.展开更多
For target tracking and localization in bearing-only sensor network,it is an essential and significant challenge to solve the problem of plug-and-play expansion while stably enhancing the accuracy of state estimation....For target tracking and localization in bearing-only sensor network,it is an essential and significant challenge to solve the problem of plug-and-play expansion while stably enhancing the accuracy of state estimation.This paper pro-poses a distributed state estimation method based on two-layer factor graph.Firstly,the measurement model of the bearing-only sensor network is constructed,and by investigating the observ-ability and the Cramer-Rao lower bound of the system model,the preconditions are analyzed.Subsequently,the location fac-tor graph and cubature information filtering algorithm of sensor node pairs are proposed for localized estimation.Building upon this foundation,the mechanism for propagating confidence mes-sages within the fusion factor graph is designed,and is extended to the entire sensor network to achieve global state estimation.Finally,groups of simulation experiments are con-ducted to compare and analyze the results,which verifies the rationality,effectiveness,and superiority of the proposed method.展开更多
In this paper,a feature selection method for determining input parameters in antenna modeling is proposed.In antenna modeling,the input feature of artificial neural network(ANN)is geometric parameters.The selection cr...In this paper,a feature selection method for determining input parameters in antenna modeling is proposed.In antenna modeling,the input feature of artificial neural network(ANN)is geometric parameters.The selection criteria contain correlation and sensitivity between the geometric parameter and the electromagnetic(EM)response.Maximal information coefficient(MIC),an exploratory data mining tool,is introduced to evaluate both linear and nonlinear correlations.The EM response range is utilized to evaluate the sensitivity.The wide response range corresponding to varying values of a parameter implies the parameter is highly sensitive and the narrow response range suggests the parameter is insensitive.Only the parameter which is highly correlative and sensitive is selected as the input of ANN,and the sampling space of the model is highly reduced.The modeling of a wideband and circularly polarized antenna is studied as an example to verify the effectiveness of the proposed method.The number of input parameters decreases from8 to 4.The testing errors of|S_(11)|and axis ratio are reduced by8.74%and 8.95%,respectively,compared with the ANN with no feature selection.展开更多
采用重庆地区34个气象观测站1971—2000年30 a平均月降水总量资料,以及重庆地区100 m×100 m DEM(D igital E levation Model)数据,对重庆地区降水空间分布进行研究。根据山地气候学原理,利用GIS(Geographical Information Systems...采用重庆地区34个气象观测站1971—2000年30 a平均月降水总量资料,以及重庆地区100 m×100 m DEM(D igital E levation Model)数据,对重庆地区降水空间分布进行研究。根据山地气候学原理,利用GIS(Geographical Information Systems)软件,分析降水空间分布的影响因子,建立平均月降水量空间估算模型,计算了平均月降水量的空间分布。结果表明:随着海拔高度的增加,降水量逐渐增加;各月降水量的最大值出现在东北山区;降水量的季节变化明显。展开更多
高频地波雷达的"距离-多普勒"(Range-Doppler,R-D)数据与"恒虚警率"(Constant False-AlarmRate,CFAR)检测结果数据存在非直观性的问题,本文针对此问题,分析了地波雷达回波数据特点以及结果形式,研究了采用地理信息...高频地波雷达的"距离-多普勒"(Range-Doppler,R-D)数据与"恒虚警率"(Constant False-AlarmRate,CFAR)检测结果数据存在非直观性的问题,本文针对此问题,分析了地波雷达回波数据特点以及结果形式,研究了采用地理信息系统(Geographic Information System,GIS)技术对回波数据进行显示分析,对R-D与CFAR检测结果进行表达,实现高频数据在GIS环境下的表达处理与显示。本文采用GIS的栅格表达"距离-多普勒"数据,采用矢量数据结构表达CFAR检测结果,实现了地波雷达检测信息的直观显示;研究了高频地波雷达数据中特定距离一维谱信号的提取,实现了基于距离值的目标CFAR检测查询;针对雷达数据量大、处理时间长的问题,采用多线程处理机制实现了高效实时显示和分析。展开更多
海域定级是采用定性和定量的方法将同一类型用海划分为不同级别,是海域管理最基础性的工作,对于科学合理地开发和利用海岸带资源至关重要。本研究以Visual Studio 2010为开发平台,采用C语言,结合嵌入式ArcEngine组件库,集成设计实现海...海域定级是采用定性和定量的方法将同一类型用海划分为不同级别,是海域管理最基础性的工作,对于科学合理地开发和利用海岸带资源至关重要。本研究以Visual Studio 2010为开发平台,采用C语言,结合嵌入式ArcEngine组件库,集成设计实现海洋领域具有较高专业性和实用性的海域定级系统。该系统采用海洋公益领域专家制定的指标体系,通过数据的管理、集成和分析,实现了海域定级相关方面的功能。该系统将海域定级原理与地理信息系统(Geographic Information System,GIS)技术相结合,为海域基层部门提高工作效率、实现海岸带资源科学有效管理提供了依据。展开更多
基金supported by the Fundamental Research Funds for the Central Universities(WK3490000006).
文摘Lossy image coding is the art of computing that is principally bounded by the image’s rate-distortion function.This bound,though never accurately characterized,has been approached practically via deep learning technologies in recent years.Indeed,learned image coding schemes allow direct optimization of the joint rate-distortion cost,thereby outperforming the handcrafted image coding schemes by a large margin.Still,it is observed that there is room for further improvement in the rate-distortion performance of learned image coding.In this article,we identify the gap between the ideal rate-distortion function forecasted by Shannon’s information theory and the empirical rate-distortion function achieved by the state-of-the-art learned image coding schemes,revealing that the gap is incurred by five different effects:modeling effect,approximation effect,amortization effect,digitization effect,and asymptotic effect.We design simulations and experiments to quantitatively evaluate the last three effects,which demonstrates the high potential of future lossy image coding technologies.
文摘This paper proposes a novel Range Migration Algorithm(RMA)integrated with an adaptive background filtering method specifically designed for near-field millimeter-wave imaging scenarios where targets are in close proximity to background structures.This method simulates the attention distribution mode of the human visual system which is used in Artificial Intelligence(AI)and called the Attention Mechanism.Based on the concept of static clutter filtering,the frequency-domain signals of the scanning aperture are divided into grid cells.Background scattering functions are established by analyzing the motion processes within each cell,and the background interference is linearly filtered out.An analysis of the manifestation of background scattering interference within the algorithm is carried out,and the impact of the grid cell dimension on the imaging quality is investigated.Experimental results show that the proposed method exhibits the capability to enhance the signal-to-noise ratio of both the target and the background.It effectively suppresses the background interference,leading to a more prominent image,meanwhile without imposing the excessive computational load.The method offers a novel solution for improving the performance of millimeter-wave imaging technology in practical applications.
文摘2025年12月22日,上海交通大学医学院医学技术学院李文杰在人工智能与信息融合领域国际顶级期刊Information Fusion发表了一项研究成果“CX-Mind:a pioneering multimodal large language model for interleaved reasoning in chest X-ray via curriculum-guided reinforcement learning”。
基金financial support provided by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)+1 种基金the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.
基金supported by the National Natural Science Foundation of China(Grant No.61773142).
文摘Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an integrated approach that combines a Three-Dimensional Finite-Time Optimal Cooperative Guidance Law(FTOC)with an Information Fusion Anti-saturation Predefined-time Observer(IFAPO).The proposed FTOC guidance law employs a nonlinear,non-quadratic finite-time optimal control strategy designed for rapid convergence within the limited timeframes of near-space interceptions,avoiding the need for remaining flight time estimation or linear decoupling inherent in traditional methods.To complement the guidance strategy,the IFAPO leverages multi-source information fusion theory and incorporates anti-saturation mechanisms to enhance target maneuver estimation.This method ensures accurate and real-time prediction of target acceleration while maintaining predefined convergence performance,even under complex interception conditions.By integrating the FTOC guidance law and IFAPO,the approach optimizes cooperative missile positioning,improves interception success rates,and minimizes fuel consumption,addressing practical constraints in military applications.Simulation results and comparative analyses confirm the effectiveness of the integrated approach,demonstrating its capability to achieve cooperative interception of highly maneuvering targets with enhanced efficiency and reduced economic costs,aligning with realistic combat scenarios.
基金supported by the Aeronautical Science Foundation of China(2020Z023053002).
文摘High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelationships among intricate variable patterns.Accordingly,this study proposes a Mogrifier gate recurrent unit-D(Mog-GRU-D)model to address the com-bat target intention prediction issue under the incomplete infor-mation condition.The proposed model directly processes miss-ing data while reducing the independence between inputs and output states.A total of 1200 samples from twelve continuous moments are captured through the combat simulation system,each of which consists of seven dimensional features.To bench-mark the experiment,a missing valued dataset has been gener-ated by randomly removing 20%of the original data.Extensive experiments demonstrate that the proposed model obtains the state-of-the-art performance with an accuracy of 73.25%when dealing with incomplete information.This study provides possi-ble interpretations for the principle of target interactive mecha-nism,highlighting the model’s effectiveness in potential air war-fare implementation.
基金supported by the National Natural Science Foundation of China(62222212).
文摘Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the context of fewshot and zero-shot scenarios remains highly challenging due to the scarcity of training data.Large language models(LLMs),on the other hand,can generalize well to unseen tasks with few-shot demonstrations or even zero-shot instructions and have demonstrated impressive ability for a wide range of natural language understanding or generation tasks.Nevertheless,it is unclear,whether such effectiveness can be replicated in the task of IE,where the target tasks involve specialized schema and quite abstractive entity or relation concepts.In this paper,we first examine the validity of LLMs in executing IE tasks with an established prompting strategy and further propose multiple types of augmented prompting methods,including the structured fundamental prompt(SFP),the structured interactive reasoning prompt(SIRP),and the voting-enabled structured interactive reasoning prompt(VESIRP).The experimental results demonstrate that while directly promotes inferior performance,the proposed augmented prompt methods significantly improve the extraction accuracy,achieving comparable or even better performance(e.g.,zero-shot FewNERD,FewNERD-INTRA)than state-of-theart methods that require large-scale training samples.This study represents a systematic exploration of employing instruction-following LLM for the task of IE.It not only establishes a performance benchmark for this novel paradigm but,more importantly,validates a practical technical pathway through the proposed prompt enhancement method,offering a viable solution for efficient IE in low-resource settings.
基金supported by the National Natural Science Foundation of China(72374061)the Ministry of Education Humanities and Social Science Research Youth Project(22YJC630056)+2 种基金the Anhui Provincial Natural Science Foundation(2208085UD02)the Scientific Research Fund of the Hunan Provincial Education Department(23C0677)the Changsha Municipal Planning Project of Philosophy and Social Sciences(2025CSSKKT25)。
文摘The transportation sector’s reliance on petroleum fuels exacerbates environmental issues,emphasizing the need for sustainable development.Online electric vehicle(EV)car-hailing services present a key opportunity for EV adoption.This study develops a model based on heuristic and systematic information processing,examining the impacts of factors such as perceived risk,information need,and experience and knowledge on users’utilization of online electric vehicle carhailing services.The results indicate that users’experience and knowledge increase their information need and promote both heuristic and systematic processing,leading to positive attitude change,although they don’t significantly affect perceived risk.Perceived risk increases information need and supports supports systematic processing but negatively impacts attitude change.Greater information enhances systematic processing and attitude change.Perceived risk and information need do not affect attitude change via heuristic processing.Finally,the paper concludes with implications and directions for future research.
基金supported by the National Natural Science Foundation of China(62176214).
文摘For target tracking and localization in bearing-only sensor network,it is an essential and significant challenge to solve the problem of plug-and-play expansion while stably enhancing the accuracy of state estimation.This paper pro-poses a distributed state estimation method based on two-layer factor graph.Firstly,the measurement model of the bearing-only sensor network is constructed,and by investigating the observ-ability and the Cramer-Rao lower bound of the system model,the preconditions are analyzed.Subsequently,the location fac-tor graph and cubature information filtering algorithm of sensor node pairs are proposed for localized estimation.Building upon this foundation,the mechanism for propagating confidence mes-sages within the fusion factor graph is designed,and is extended to the entire sensor network to achieve global state estimation.Finally,groups of simulation experiments are con-ducted to compare and analyze the results,which verifies the rationality,effectiveness,and superiority of the proposed method.
基金National Natural Science Foundation of China(62161048)Sichuan Science and Technology Program(2022NSFSC0547,2022ZYD0109)。
文摘In this paper,a feature selection method for determining input parameters in antenna modeling is proposed.In antenna modeling,the input feature of artificial neural network(ANN)is geometric parameters.The selection criteria contain correlation and sensitivity between the geometric parameter and the electromagnetic(EM)response.Maximal information coefficient(MIC),an exploratory data mining tool,is introduced to evaluate both linear and nonlinear correlations.The EM response range is utilized to evaluate the sensitivity.The wide response range corresponding to varying values of a parameter implies the parameter is highly sensitive and the narrow response range suggests the parameter is insensitive.Only the parameter which is highly correlative and sensitive is selected as the input of ANN,and the sampling space of the model is highly reduced.The modeling of a wideband and circularly polarized antenna is studied as an example to verify the effectiveness of the proposed method.The number of input parameters decreases from8 to 4.The testing errors of|S_(11)|and axis ratio are reduced by8.74%and 8.95%,respectively,compared with the ANN with no feature selection.
文摘采用重庆地区34个气象观测站1971—2000年30 a平均月降水总量资料,以及重庆地区100 m×100 m DEM(D igital E levation Model)数据,对重庆地区降水空间分布进行研究。根据山地气候学原理,利用GIS(Geographical Information Systems)软件,分析降水空间分布的影响因子,建立平均月降水量空间估算模型,计算了平均月降水量的空间分布。结果表明:随着海拔高度的增加,降水量逐渐增加;各月降水量的最大值出现在东北山区;降水量的季节变化明显。
文摘高频地波雷达的"距离-多普勒"(Range-Doppler,R-D)数据与"恒虚警率"(Constant False-AlarmRate,CFAR)检测结果数据存在非直观性的问题,本文针对此问题,分析了地波雷达回波数据特点以及结果形式,研究了采用地理信息系统(Geographic Information System,GIS)技术对回波数据进行显示分析,对R-D与CFAR检测结果进行表达,实现高频数据在GIS环境下的表达处理与显示。本文采用GIS的栅格表达"距离-多普勒"数据,采用矢量数据结构表达CFAR检测结果,实现了地波雷达检测信息的直观显示;研究了高频地波雷达数据中特定距离一维谱信号的提取,实现了基于距离值的目标CFAR检测查询;针对雷达数据量大、处理时间长的问题,采用多线程处理机制实现了高效实时显示和分析。
文摘海域定级是采用定性和定量的方法将同一类型用海划分为不同级别,是海域管理最基础性的工作,对于科学合理地开发和利用海岸带资源至关重要。本研究以Visual Studio 2010为开发平台,采用C语言,结合嵌入式ArcEngine组件库,集成设计实现海洋领域具有较高专业性和实用性的海域定级系统。该系统采用海洋公益领域专家制定的指标体系,通过数据的管理、集成和分析,实现了海域定级相关方面的功能。该系统将海域定级原理与地理信息系统(Geographic Information System,GIS)技术相结合,为海域基层部门提高工作效率、实现海岸带资源科学有效管理提供了依据。
