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Empirical tropospheric zenith wet delay models with strong generalization capability based on a robust machine learning fusion algorithm 认领 引用
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作者 Jiahao Zhang Qin Liang Yunqing Huang 《Geodesy and Geodynamics》 EI CSCD 2026年第2期211-224,共14页
Tropospheric zenith wet delay(ZWD)plays a vital role in the analysis of space geodetic observations.In recent years,machine learning methods have been increasingly applied to improve the accuracy of ZWD calculations.H... Tropospheric zenith wet delay(ZWD)plays a vital role in the analysis of space geodetic observations.In recent years,machine learning methods have been increasingly applied to improve the accuracy of ZWD calculations.However,a single machine learning model has limited generalization capabilities.To address these limitations,this study introduces a novel machine learning fusion(MLF)algorithm with stronger generalization capabilities to enhance ZWD modeling and prediction accuracy.The MLF algorithm utilizes a two-layer structure integrating extra trees(ET),backpropagation neural network(BPNN),and linear regression models.By comparing the root mean square error(RMSE)of these models,we found that both ET-based and MLF-based models outperform RF-based and BPNN-based models in terms of internal and external accuracy,across both surface meteorological data-based and blind models.The improvement in exte rnal accuracy is particularly significant in the blind models.Our re sults show that the MLF(with an RMSE of 3.93 cm)and ET(3.99 cm)models outperform the traditional GPT3model(4.07 cm),while the RF(4.21 cm)and BPNN(4.14 cm)have worse external accuracies than the GPT3 model.It is worth noting that the BPNN suffered from overfitting during external accuracy tests,which was avoided by the MLF.In summary,regardless of the availability of surface meteorological data,the MLF-based empirical models demonstrate superior internal and external accuracy compared to the other tested models in this study. 展开更多
关键词 Tropospheric zenith wet delay Machine learning Extra trees Machine learning fusion algorithm Empirical models
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Fusion Algorithm Based on Improved A*and DWA for USV Path Planning 认领 引用 被引量：2
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作者 Changyi Li Lei Yao Chao Mi 《哈尔滨工程大学学报（英文版）》 CSCD 2025年第1期224-237,共14页
The traditional A*algorithm exhibits a low efficiency in the path planning of unmanned surface vehicles(USVs).In addition,the path planned presents numerous redundant inflection waypoints,and the security is low,wh... The traditional A*algorithm exhibits a low efficiency in the path planning of unmanned surface vehicles(USVs).In addition,the path planned presents numerous redundant inflection waypoints,and the security is low,which is not conducive to the control of USV and also affects navigation safety.In this paper,these problems were addressed through the following improvements.First,the path search angle and security were comprehensively considered,and a security expansion strategy of nodes based on the 5×5 neighborhood was proposed.The A*algorithm search neighborhood was expanded from 3×3 to 5×5,and safe nodes were screened out for extension via the node security expansion strategy.This algorithm can also optimize path search angles while improving path security.Second,the distance from the current node to the target node was introduced into the heuristic function.The efficiency of the A*algorithm was improved,and the path was smoothed using the Floyd algorithm.For the dynamic adjustment of the weight to improve the efficiency of DWA,the distance from the USV to the target point was introduced into the evaluation function of the dynamic-window approach(DWA)algorithm.Finally,combined with the local target point selection strategy,the optimized DWA algorithm was performed for local path planning.The experimental results show the smooth and safe path planned by the fusion algorithm,which can successfully avoid dynamic obstacles and is effective and feasible in path planning for USVs. 展开更多
关键词 Improved A*algorithm Optimized DWA algorithm Unmanned surface vehicles Path planning Fusion algorithm
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Multi-sensor Hybrid Fusion Algorithm Based on Adaptive Square-root Cubature Kalman Filter 认领 引用 被引量：6
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作者 Xiaogong Lin Shusheng Xu Yehai Xie 《Journal of Marine Science and Application》 2013年第1期106-111,共6页
In the normal operation condition,a conventional square-root cubature Kalman filter(SRCKF)gives sufficiently good estimation results.However,if the measurements are not reliable,the SRCKF may give inaccurate results a... In the normal operation condition,a conventional square-root cubature Kalman filter(SRCKF)gives sufficiently good estimation results.However,if the measurements are not reliable,the SRCKF may give inaccurate results and diverges by time.This study introduces an adaptive SRCKF algorithm with the filter gain correction for the case of measurement malfunctions.By proposing a switching criterion,an optimal filter is selected from the adaptive and conventional SRCKF according to the measurement quality.A subsystem soft fault detection algorithm is built with the filter residual.Utilizing a clear subsystem fault coefficient,the faulty subsystem is isolated as a result of the system reconstruction.In order to improve the performance of the multi-sensor system,a hybrid fusion algorithm is presented based on the adaptive SRCKF.The state and error covariance matrix are also predicted by the priori fusion estimates,and are updated by the predicted and estimated information of subsystems.The proposed algorithms were applied to the vessel dynamic positioning system simulation.They were compared with normal SRCKF and local estimation weighted fusion algorithm.The simulation results show that the presented adaptive SRCKF improves the robustness of subsystem filtering,and the hybrid fusion algorithm has the better performance.The simulation verifies the effectiveness of the proposed algorithms. 展开更多
关键词 hybrid fusion algorithm square-root cubature Kalmanfilter adaptive filter fault detection
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A new PQ disturbances identification method based on combining neural network with least square weighted fusion algorithm 认领 引用
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作者 LV Gan-yun CHENG Hao-zhong +1 位作者 ZHA Hai-bao 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2006年第6期649-653,共5页
A new method for power quality(PQ)disturbances identification is brought forward based on combining a neural network with least square(LS)weighted fusion algorithm.The characteristic components of PQ disturbances are ... A new method for power quality(PQ)disturbances identification is brought forward based on combining a neural network with least square(LS)weighted fusion algorithm.The characteristic components of PQ disturbances are distilled through an improved phase-located loop(PLL)system at first,and then five child BP ANNs with different structures are trained and adopted to identify the PQ disturbances respectively.The combining neural network fuses the identification results of these child ANNs with LS weighted fusion algorithm,and identifies PQ disturbances with the fused result finally.Compared with a single neural network,the combining one with LS weighted fusion algorithm can identify the PQ disturbances correctly when noise is strong.However,a single neural network may fail in this case.Furthermore,the combining neural network is more reliable than a single neural network.The simulation results prove the conclusions above. 展开更多
关键词 PQ disturbances identification combining neural network LS weighted fusion algorithm improved PLL system
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An Improved Medical Image Fusion Algorithm for Anatomical and Functional Medical Images 认领 引用 被引量：2
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作者 CHEN Mei-ling TAO Ling QIAN Zhi-yu 《Chinese Journal of Biomedical Engineering(English Edition)》 CAS 2009年第2期84-92,共9页
In recent years,many medical image fusion methods had been exploited to derive useful information from multimodality medical image data,but,not an appropriate fusion algorithm for anatomical and functional medical ima... In recent years,many medical image fusion methods had been exploited to derive useful information from multimodality medical image data,but,not an appropriate fusion algorithm for anatomical and functional medical images.In this paper,the traditional method of wavelet fusion is improved and a new fusion algorithm of anatomical and functional medical images,in which high-frequency and low-frequency coefficients are studied respectively.When choosing high-frequency coefficients,the global gradient of each sub-image is calculated to realize adaptive fusion,so that the fused image can reserve the functional information;while choosing the low coefficients is based on the analysis of the neighborbood region energy,so that the fused image can reserve the anatomical image's edge and texture feature.Experimental results and the quality evaluation parameters show that the improved fusion algorithm can enhance the edge and texture feature and retain the function information and anatomical information effectively. 展开更多
关键词 medical image fusion wavelet transform fusion algorithm quality evaluation
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Adaptive Multisensor Tracking Fusion Algorithm for Air-borne Distributed Passive Sensor Network 认领 引用
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作者 Zhen Ding Hongcai Zhang & Guanzhong Dai 《Journal of Systems Engineering and Electronics》 1996年第3期15-23,共9页
Single passive sensor tracking algorithms have four disadvantages: bad stability, longdynamic time, big bias and sensitive to initial conditions. So the corresponding fusion algorithm results in bad performance. A new... Single passive sensor tracking algorithms have four disadvantages: bad stability, longdynamic time, big bias and sensitive to initial conditions. So the corresponding fusion algorithm results in bad performance. A new error analysis method for two passive sensor tracking system is presented and the error equations are deduced in detail. Based on the equations, we carry out theoretical computation and Monte Carlo computer simulation. The results show the correctness of our error computation equations. With the error equations, we present multiple 'two station'fusion algorithm using adaptive pseudo measurement equations. This greatly enhances the tracking performance and makes the algorithm convergent very fast and not sensitive to initial conditions.Simulation results prove the correctness of our new algorithm. 展开更多
关键词 Passive tracking system Error analysis Fusion algorithm Distributed passive sensornetwork Distributed estimation.
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Identification of small impact craters in Chang’e-4 landing areas using a new multi-scale fusion crater detection algorithm 认领 引用
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作者 FangChao Liu HuiWen Liu +7 位作者 Li Zhang Jian Chen DiJun Guo Bo Li ChangQing Liu ZongCheng Ling Ying-Bo Lu JunSheng Yao 《Earth and Planetary Physics》 EI CSCD 2026年第1期92-104,共13页
Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious an... Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy. 展开更多
关键词 impact craters Chang’e-4 landing area multi-scale automatic detection YOLO11 Fusion algorithm
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Flight parameter detection via a pressure-velocity fusion algorithm with a flexible sensing patch 认领 引用
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作者 Zhichao Ma Yingli Shi Guozhen Shen 《Science China Materials》 SCIE EI CAS CSCD 2026年第6期3712-3713,共2页
Precise measurement of flight parameters—including angle of attack(AOA),angle of sideslip(AOS),and airspeed—is critical for stabilized control of unmanned aerial vehicle(UAV)operating in complex aerodynamic environm... Precise measurement of flight parameters—including angle of attack(AOA),angle of sideslip(AOS),and airspeed—is critical for stabilized control of unmanned aerial vehicle(UAV)operating in complex aerodynamic environments[1].Conventional rigid sensors struggle to conform to curved leading edges,disrupting local flow and degrading aerodynamic performance[2]. 展开更多
关键词 flight parameters measurement flight parameters including pressure velocity fusion algorithm flexible sensing patch unmanned aerial vehicle uav operating angle attack angle sideslip stabilized control
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An analytical pressure-velocity fusion algorithm-empowered flexible sensing patch for flight parameter detection 认领 引用 被引量：1
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作者 Yunfan Li Zihao Dong +6 位作者 Zheng Gong Zhiqiang Ma Xin Ke Tianyu Sheng Xiaochang Yang Xilun Ding Yonggang Jiang 《npj Flexible Electronics》 SCIE CSCD 2025年第1期1025-1032,共8页
Flexible sensing array integrated with multiple sensors is an attractive approach for flight parameter detection.However,the poor resolution of flexible sensors and time-consuming neural network processes mitigate the... Flexible sensing array integrated with multiple sensors is an attractive approach for flight parameter detection.However,the poor resolution of flexible sensors and time-consuming neural network processes mitigate their accuracy and adaptability in predicting flight parameters.Here we present an ultra-thin flexible sensing patch with a new configuration,comprising a differential pressure sensor array and a vector flow velocity sensor.The capacitive differential pressure sensor array is fabricated by a multilayer polyimide bonding technique,reaching a resolution of 0.14 Pa.To solve flight parameters with the flexible sensing patch,we develop an analytical pressure-velocity fusion algorithm,enabling fast response and high accuracy in flight parameter detection.The average errors in calculating the angle of attack,angle of sideslip,and airspeed are 0.22°,0.35°,and 0.73 m s-1,respectively.The high-resolution flexible sensors and novel analytical pressure-velocity fusion algorithm pave the way for flexible sensing patch-based air data sensing techniques. 展开更多
关键词 analytical pressure velocity fusion algorithm flight parameter detectionhoweverthe vector flow velocity sensorthe flexible sensing array flexible sensing patch flexible sensors differential pressure sensor array neural network processes
Optimized Deployment Method for Finite Access Points Based on Virtual Force Fusion Bat Algorithm 认领 引用
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作者 Jian Li Qing Zhang +2 位作者 Tong Yang Yu’an Chen Yongzhong Zhan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第9期3029-3051,共23页
In the deployment of wireless networks in two-dimensional outdoor campus spaces,aiming at the problem of efficient coverage of the monitoring area by limited number of access points(APs),this paper proposes a deployme... In the deployment of wireless networks in two-dimensional outdoor campus spaces,aiming at the problem of efficient coverage of the monitoring area by limited number of access points(APs),this paper proposes a deployment method of multi-objective optimization with virtual force fusion bat algorithm(VFBA)using the classical four-node regular distribution as an entry point.The introduction of Lévy flight strategy for bat position updating helps to maintain the population diversity,reduce the premature maturity problem caused by population convergence,avoid the over aggregation of individuals in the local optimal region,and enhance the superiority in global search;the virtual force algorithm simulates the attraction and repulsion between individuals,which enables individual bats to precisely locate the optimal solution within the search space.At the same time,the fusion effect of virtual force prompts the bat individuals to move faster to the potential optimal solution.To validate the effectiveness of the fusion algorithm,the benchmark test function is selected for simulation testing.Finally,the simulation result verifies that the VFBA achieves superior coverage and effectively reduces node redundancy compared to the other three regular layout methods.The VFBA also shows better coverage results when compared to other optimization algorithms. 展开更多
关键词 Multi-objective optimization deployment virtual force algorithm bat algorithm fusion algorithm
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A novel image fusion algorithm based on bandelet transform 认领 引用 被引量：12
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作者 屈小波 闫敬文 +2 位作者 谢国富 朱自谦 陈本刚 《Chinese Optics Letters》 SCIE EI CAS 2007年第10期569-572,共4页
A novel image fusion algorithm based on bandelet transform is proposed. Bandelet transform can take advantage of the geometrical regularity of image structure and represent sharp image transitions such as edges effici... A novel image fusion algorithm based on bandelet transform is proposed. Bandelet transform can take advantage of the geometrical regularity of image structure and represent sharp image transitions such as edges efficiently in image fusion. For reconstructing the fused image, the maximum rule is used to select source images＇ geometric flow and bandelet coefficients. Experimental results indicate that the bandelet-based fusion algorithm represents the edge and detailed information well and outperforms the wavelet-based and Laplacian pyramid-based fusion algorithms, especially when the abundant texture and edges are contained in the source images. 展开更多
关键词 A novel image fusion algorithm based on bandelet transform
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Prediction and fusion algorithm for meat moisture content measurement based on loss-on-drying method 认领 引用
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作者 Jing Ling Jie Xu +1 位作者 Haijun Lin Jinyuan Lin 《International Journal of Agricultural and Biological Engineering》 SCIE 2020年第4期198-204,共7页
The loss-on-drying method has been widely used as a standard approach for measuring the moisture content of high-moisture materials such as solid and semi-solid foods.Loss-on-drying method provides reliable results,wh... The loss-on-drying method has been widely used as a standard approach for measuring the moisture content of high-moisture materials such as solid and semi-solid foods.Loss-on-drying method provides reliable results,whilst usually labor-intensive and time-consuming.This paper presents a novel algorithm for predicting the moisture content of meats based on the loss-on drying method.The proposed approach developed a drying kinetics model of meats based on Fick’s Second Law and designed a prediction algorithm for meat moisture content using the least-squares method.The predicted results were compared with the official method recommended by the Association of Official Analytical Chemists(AOAC).When the moisture content of meat samples(beef and pork)was varied from 69.46%to 74.21%,the relative error of the meat moisture content(MMC)calculated by the proposed algorithm was 0.0017-0.0117,the absolute errors were less than 1%.The testing time was about 40.18%-56.87%less than the standard detection procedure. 展开更多
关键词 meat moisture content loss-on-drying method Fick’s Second Law fusion algorithm measurement prediction
Exploring on Hierarchical Kalman Filtering Fusion Accuracy 认领 引用
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作者 罗森林 张鹤飞 潘丽敏 《Journal of Beijing Institute of Technology》 EI CAS 1998年第4期373-379,共7页
Aim To analyze the traditional hierarchical Kalman filtering fusion algorithm theoretically and point out that the traditional Kalman filtering fusion algorithm is complex and can not improve the tracking precision we... Aim To analyze the traditional hierarchical Kalman filtering fusion algorithm theoretically and point out that the traditional Kalman filtering fusion algorithm is complex and can not improve the tracking precision well, even it is impractical, and to propose the weighting average fusion algorithm. Methods The theoretical analysis and Monte Carlo simulation methods were ed to compare the traditional fusion algorithm with the new one,and the comparison of the root mean square error statistics values of the two algorithms was made. Results The hierarchical fusion algorithm is not better than the weighting average fusion and feedback weighting average algorithm The weighting filtering fusion algorithm is simple in principle, less in data, faster in processing and better in tolerance.Conclusion The weighting hierarchical fusion algorithm is suitable for the defective sensors.The feedback of the fusion result to the single sersor can enhance the single sensorr's precision. especially once one sensor has great deviation and low accuracy or has some deviation of sample period and is asynchronous to other sensors. 展开更多
关键词 Kalman filtering hierarchical fusion algorithm weighting average feedback fusion algorithm
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移动机器人路径规划算法综述 认领 引用 被引量：7
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作者 张永宏 郭子健 +2 位作者 陆竹恒 蒋亮 曹海啸 《计算机工程与应用》 EI CSCD 北大核心 2026年第2期26-39,共14页
路径规划算法是实现移动机器人自主导航的关键技术之一,其性能决定了路径规划的质量。为全面地了解移动机器人路径规划算法的研究现状和发展,对常用算法进行系统综述。针对路径规划算法的特点,将其划分为传统算法、基于采样的算法、基... 路径规划算法是实现移动机器人自主导航的关键技术之一,其性能决定了路径规划的质量。为全面地了解移动机器人路径规划算法的研究现状和发展,对常用算法进行系统综述。针对路径规划算法的特点,将其划分为传统算法、基于采样的算法、基于人工智能的算法和基于智能仿生的算法;基于上述分类,简要介绍了算法原理和实际应用场景,重点阐述近年来各种算法的相关研究成果,概括对比各类算法的优缺点;选取了四种算法在同一仿真环境下验证算法的有效性。最后,对移动机器人未来发展趋势进行展望,以期为移动机器人路径规划研究提供参考。 展开更多
关键词 移动机器人 路径规划 算法分类与融合 算法验证
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Anti-swarm UAV radar system based on detection data fusion 认领 引用 被引量：3
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作者 WANG Pengfei HU Jinfeng +2 位作者 HU Wen WANG Weiguang DONG Hao 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第5期1167-1176,共10页
There is a growing body of research on the swarm unmanned aerial vehicle(UAV)in recent years,which has the characteristics of small,low speed,and low height as radar target.To confront the swarm UAV,the design of anti... There is a growing body of research on the swarm unmanned aerial vehicle(UAV)in recent years,which has the characteristics of small,low speed,and low height as radar target.To confront the swarm UAV,the design of anti-UAV radar system based on multiple input multiple output(MIMO)is put forward,which can elevate the performance of resolution,angle accuracy,high data rate,and tracking flexibility for swarm UAV detection.Target resolution and detection are the core problem in detecting the swarm UAV.The distinct advantage of MIMO system in angular accuracy measurement is demonstrated by comparing MIMO radar with phased array radar.Since MIMO radar has better performance in resolution,swarm UAV detection still has difficulty in target detection.This paper proposes a multi-mode data fusion algorithm based on deep neural networks to improve the detection effect.Subsequently,signal processing and data processing based on the detection fusion algorithm above are designed,forming a high resolution detection loop.Several simulations are designed to illustrate the feasibility of the designed system and the proposed algorithm. 展开更多
关键词 swarm radar high resolution deep neural network fusion algorithm
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无人机航迹规划算法综述 认领 引用 被引量：2
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作者 王硕 李洋 +1 位作者 赵蕴龙 刘春颜 《哈尔滨工程大学学报》 EI CAS CSCD 北大核心 2026年第3期708-719,共12页
为系统梳理无人机航迹规划领域的研究进展,本文首先对无人机航迹规划问题进行分析,依据算法原理对现有方法进行分类并介绍了其中常用算法的特点与应用;其次基于改进思路将近年研究归纳为基于算法自身局限性改进、结合环境表征改进以及... 为系统梳理无人机航迹规划领域的研究进展,本文首先对无人机航迹规划问题进行分析,依据算法原理对现有方法进行分类并介绍了其中常用算法的特点与应用;其次基于改进思路将近年研究归纳为基于算法自身局限性改进、结合环境表征改进以及基于多算法融合改进3类,最后指出航迹规划算法研究的难点与挑战以及现有研究的不足,然后在此基础上对未来发展趋势进行展望。研究结果表明,传统经典算法如A*算法、遗传算法、蚁群算法的改进已较成熟,而灰狼算法等新型智能算法以及与强化学习相结合的方法仍需深入研究。此外,当前研究主要针对单无人机场景,多机协同与复杂场景适应性仍显不足。需平衡环境建模的精度与效率,发展更贴合实际的建模方法并在此基础上优化规划算法。 展开更多
关键词 无人机 航迹规划 算法改进 强化学习 深度强化学习 群体智能 遗传算法 算法融合
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三肇凹陷A区块葡萄花油层缝网压裂参数优化实践 认领 引用
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作者 杨光 张煜琦 +2 位作者 李锦超 杨玉才 刘小波 《大庆石油地质与开发》 CAS 北大核心 2026年第1期118-126,共9页
松辽盆地三肇凹陷葡萄花油层属于典型的低孔、低渗储层,随着压裂重复次数的增多,压裂效果逐年变差。为了探究A区块葡萄花油层缝网压裂影响压裂效果的主控因素,应用聚类分析方法,对试验区块各类数据参数预处理,优选堆叠集成算法,并对压... 松辽盆地三肇凹陷葡萄花油层属于典型的低孔、低渗储层,随着压裂重复次数的增多,压裂效果逐年变差。为了探究A区块葡萄花油层缝网压裂影响压裂效果的主控因素,应用聚类分析方法,对试验区块各类数据参数预处理,优选堆叠集成算法,并对压裂效果进行评价,制作压裂参数优化图版。结果表明:应用聚类分析方法将离散型数据转化为2―4类分类变量,可保证回归算法测试集的相关系数达到83%以上;应用集成算法综合考虑不同算法的预测结果,能够提升预测准确率5百分点;三肇凹陷A区块试验井不同储层特征对应的最优施工参数差异较大,根据储层不同特征确定影响因素权重,选取权重较大的有效厚度、加砂强度等9类主控因素,建立加砂、加液优化参数图版,实际应用表明试验区块20口井的初期日增油量同比提高了30%。研究成果可为同类储层压裂选井、选层及压裂规模设计提供理论依据及方案。 展开更多
关键词 葡萄花油层 压裂效果 主控因素 聚类 融合算法 压裂参数优化
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空地网联集群协同模式识别方法 认领 引用
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作者 曲桂娴 周建山 +3 位作者 司杨 刘晓静 袁奇雨 马清琳 《北京航空航天大学学报》 EI CAS CSCD 北大核心 2026年第1期147-156,共10页
空地网联集群在智慧城市、智慧农林、智慧交通等国民经济生产领域具有巨大的应用潜力,同时在战场态势感知、空地协同打击等军事领域展现出极大的应用价值。面向空地网联集群准确感知与识别复杂环境目标的需求,建立基于模式分类概率的全... 空地网联集群在智慧城市、智慧农林、智慧交通等国民经济生产领域具有巨大的应用潜力,同时在战场态势感知、空地协同打击等军事领域展现出极大的应用价值。面向空地网联集群准确感知与识别复杂环境目标的需求,建立基于模式分类概率的全局似然函数最小化模型,提出空地网联集群的分布式学习与自适应信息融合算法,该算法包括基于梯度下降的信息扩散和基于自适应加权的信息融合2个主要步骤,形成了空地协同的模式识别方法。此外,推导出了空地网联集群协同模式识别方法的平均误差递归方程,理论证明了所提算法的误差收敛性。通过建立空地网联集群网络信息交互拓扑模型,利用雷达实测数据集进行仿真测试。仿真结果表明:集群分布式融合算法对信息估计的平均均方偏差和系统误差可有效逼近理论最优水平。当节点数由10上升至40时,集群分布式融合算法的平均均方偏差由-48.70 dB下降至-53.96 dB,系统误差由-27.42 dB下降至-30.22 dB,接近于误差的理论值。对比实验表明:所提算法较传统方法具有良好的精度,可有力支撑空地网联集群对复杂环境目标的感知与识别。 展开更多
关键词 空地网联集群 协同模式识别 信息交互拓扑模型 分布式融合算法 雷达实测数据
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制造装备运动部件空间位姿检测技术研究 认领 引用
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作者 陈衡 袁明记 +1 位作者 许耀宇 夏仰球 《组合机床与自动化加工技术》 北大核心 2026年第2期151-155,162,共5页
针对辐射、密闭、剧毒等极端环境下制造装备运动部件空间位姿精度难以测试的问题,发展基于惯性测量单元的线性运动轴线六自由度误差在线测量技术,构建位置、姿态及其角速率和角加速率的融合算法,研制基于加速度传感器、陀螺仪及水平仪... 针对辐射、密闭、剧毒等极端环境下制造装备运动部件空间位姿精度难以测试的问题,发展基于惯性测量单元的线性运动轴线六自由度误差在线测量技术,构建位置、姿态及其角速率和角加速率的融合算法,研制基于加速度传感器、陀螺仪及水平仪的密闭空间内置式测试系统。然后以二维平台直线轴为测试对象,开展线性运动轴线六自由度误差检测试验,通过自研检测系统与XM60型激光干涉仪测试数据的比对分析验证了制造装备运动部件空间位姿检测技术的可行性和准确性。 展开更多
关键词 空间位姿 惯性测量单元 加速度传感器 融合算法
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四驱车辆多信息自适应融合纵向状态估计方法 认领 引用
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作者 周道林 王翔宇 +3 位作者 屈新田 万若里 邵东 李亮 《机械工程学报》 EI CAS CSCD 北大核心 2026年第8期157-168,共12页
针对四驱车辆在复杂工况下纵向状态难以准确估计、影响牵引力控制系统(Traction control system,TCS)性能的问题,提出一种融合多传感器信息、轮胎非线性附着特性与轮速稳定性信息的自适应纵向状态估计算法(Multi-source information ada... 针对四驱车辆在复杂工况下纵向状态难以准确估计、影响牵引力控制系统(Traction control system,TCS)性能的问题,提出一种融合多传感器信息、轮胎非线性附着特性与轮速稳定性信息的自适应纵向状态估计算法(Multi-source information adaptive fusion algorithm,MIAFA)。该方法根据信号可信度,自适应融合基于动力学模型的纵向加速度与基于轮速信号的纵向速度估计结果,提高了纵向状态估计精度。在轮胎打滑工况下,考虑其非线性力学特性,基于纵向滑移率与侧偏角构建了非线性附着模型,并融合惯性测量单元与转向角等传感器数据,实现纵/侧向附着的统一建模。随后,利用卡尔曼滤波估计附着系数与轮胎力,并基于动力学模型实现车辆纵向加速度计算。为增强算法在复杂工况下的适应性,构建了基于轮胎滑移率与加速度的轮速稳定性相图,基于轮速传感器信息实现了车辆纵向速度计算。仿真与实车试验结果表明,所提方法能在低附着与复杂驱动-制动-转向联合工况下有效提升纵向状态估计精度,从而增强四驱车辆TCS的控制性能。 展开更多
关键词 四驱车辆 驱动防滑控制 纵向状态估计 轮胎力估计 多信息融合算法
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