The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)den...The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)denial conditions.Therefore,this paper proposes a UAV Clusters Information Geometry Fusion Positioning(UC-IGFP)method using pseudoranges from the LEO satellites.A novel graph model for linking and computing between the UAV clusters and LEO satellites was established.By utilizing probability to describe the positional states of UAVs and sensor errors,the distributed multivariate Probability Fusion Cooperative Positioning(PF-CP)algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster.Criteria to select the centroid of the cluster were set.A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory,which overcomes the discontinuity problem caused by the change of cluster centroids.Finally,the UC-IGFP method achieves the LEO continuous highprecision positioning of UAV clusters.The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster.It significantly improves the accuracy and reliability of LEO-UAV cluster positioning.The results of comprehensive simulation experiments show that the proposed method has a 30.5%improvement in performance over the mainstream positioning methods,with a positioning error of 14.267 m.展开更多
An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Sin...An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.展开更多
The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic mismatch.In this s...The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic mismatch.In this study,a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed,where Wi-Fi,PDR,and geomagnetic signals are integrated to improve indoor positioning performances.One important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter algorithm.During the positioning process,an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range respectively.The position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected,which made up for the shortage of only one time of geomagnetic correction in the existing particle filter algorithm.In addition,this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving,which satisfies the real-time requirement of our fusion positioning approach.Through experimental verification,the average positioning accuracy of the proposed approach reaches 1.59 m,which improves 33.2%compared with the existing particle filter fusion positioning algorithms.展开更多
NaGlobal vigation Satellite System(GNSS)positioning technology is widely used for its high precision,global,and all-weather service.However,in complex environments such as urban canyons,GNSS performance is often degra...NaGlobal vigation Satellite System(GNSS)positioning technology is widely used for its high precision,global,and all-weather service.However,in complex environments such as urban canyons,GNSS performance is often degraded due to signal occlusion and even fails to achieve positioning due to the insufficient visible satellites.Because of the characteristics of large band-width,low latency,and high Base Station(BS)density,the fifth-Generation mobile communication(5G)technology has gradually become a trend for positioning in cities while offering traditional communication service.To supply the communication demands of the User Equipment(UE),only one BS is usually considered to establish a connection with the UE during the BS construction.However,the positioning accuracy with a single BS in urban canyons will be significantly reduced.To further improve the positioning accuracy in such extreme scenarios,this paper proposes a simplified 5G/GNSS fusion positioning system architecture using observations from only a 5G BS and a GNSS satellite.In this system,the GNSS receiver is mounted on the 5G BS,and the measurements provided by the receiver are used to form the differential code and complete the position estimation.The positioning mathematical models of the system based on the original code and differential code are derived.Then,the impacts of the measurements noise and the time synchronization error on the positioning accuracy are analyzed theoretically.Finally,the positioning performance is investigated by a set of simulation experiments.Numerical results show that under the existing 5G measurement noise and 2 m’s code measurement noise,the improvement of the differential code based fusion positioning compared with the 5G-only positioning is more than 32%,which is also about 6%higher than the original code based fusion positioning.Besides,this improvement is not affected by the time synchronization error between the BS and the GNSS satellite.展开更多
In order to solve the problem of limited computational resources of multi-unmanned systems airborne navigation platform,a distributed cooperative positioning method based on confidence evaluation is proposed.Firstly,t...In order to solve the problem of limited computational resources of multi-unmanned systems airborne navigation platform,a distributed cooperative positioning method based on confidence evaluation is proposed.Firstly,the impact of ranging error,priori information,spatial geometric configuration and adjacent nodes count on cooperative positioning performance are analyzed individually.Secondly,a confidence evaluation method for measurement information of adjacent nodes is designed according to the cooperative positioning principle,which comprehensively considers the coupling relationship between influencing factors.Finally,a distributed cooperative navigation filter based on inter-vehicle ranging is designed.Simulation studies show that confidence evaluation method proposed in this paper can effectively characterize the contribution of measurement information to positioning results,and positioning accuracy under the proposed method is improved by more than 15%compared with the traditional screening methods based on optimal geometric configuration and closest distance.展开更多
Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the vary...Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the varying importance of each modality across different contexts,a central and pressing challenge in multimodal sentiment analysis lies in maximizing the use of rich intra-modal features while minimizing information loss during the fusion process.In response to these critical limitations,we propose a novel framework that integrates spatial position encoding and fusion embedding modules to address these issues.In our model,text is treated as the core modality,while speech and video features are selectively incorporated through a unique position-aware fusion process.The spatial position encoding strategy preserves the internal structural information of speech and visual modalities,enabling the model to capture localized intra-modal dependencies that are often overlooked.This design enhances the richness and discriminative power of the fused representation,enabling more accurate and context-aware sentiment prediction.Finally,we conduct comprehensive evaluations on two widely recognized standard datasets in the field—CMU-MOSI and CMU-MOSEI to validate the performance of the proposed model.The experimental results demonstrate that our model exhibits good performance and effectiveness for sentiment analysis tasks.展开更多
This study proposes a Kalman filter-based indoor vehicle positioning method for cases in which the steering angle and rotation speed of the vehicle’s wheels are unknown.By fusing the position and velocity data from t...This study proposes a Kalman filter-based indoor vehicle positioning method for cases in which the steering angle and rotation speed of the vehicle’s wheels are unknown.By fusing the position and velocity data from the ultra-wideband sensors and acceleration and orientation data from the inertial measurement unit,we developed two algorithms to estimate the real-time position of the vehicle based on a linear Kalman filter and extended Kalman filter,respectively.We then conducted simulations and experiments to examine the performances of the algorithms.In the experiment,the Kalman filtering hyperparameters are configured,and we then ran the two algorithms to determine the positioning precision and accuracy with the ground truth produced via LiDAR.We verified that our method can improve precision and accuracy compared with the raw positioning data and can achieve desirable effects for indoor vehicle positioning when vehicles travel at low speeds.展开更多
An efficient vehicle detection approach is proposed for traffic surveillance images, which is based on information fusion of vehicle symmetrical contour and license plate position. The vertical symmetry axis of the ve...An efficient vehicle detection approach is proposed for traffic surveillance images, which is based on information fusion of vehicle symmetrical contour and license plate position. The vertical symmetry axis of the vehicle contour in an image is. first detected, and then the vertical and the horizontal symmetry axes of the license plate are detected using the symmetry axis of the vehicle contour as a reference. The vehicle location in an image is determined using license plate symmetry axes and the vertical and the horizontal projection maps of the vehicle edge image. A dataset consisting of 450 images （15 classes of vehicles） is used to test the proposed method. The experimental results indicate that compared with the vehicle contour-based, the license plate location-based, the vehicle texture-based and the Gabor feature-based methods, the proposed method is the best with a detection accuracy of 90.7% and an elapsed time of 125 ms.展开更多
WiFi fingerprinting is the method of recording WiFi signal strength from access points （AP） along with the positions at which they were recorded, and later matching those to new mea- surements for indoor positioning...WiFi fingerprinting is the method of recording WiFi signal strength from access points （AP） along with the positions at which they were recorded, and later matching those to new mea- surements for indoor positioning. Inertial positioning utilizes the accelerometer and gyroscopes for pedestrian positioning. However, both methods have their limitations, such as the WiFi fluctuations and the accumulative error of inertial sensors. Usually, the filtering method is used for integrating the two approaches to achieve better location accuracy. In the real environments, especially in the indoor field, the APs could be sparse and short range. To overcome the limitations, a novel particle filter approach based on Rao Blackwellized particle filter （RBPF） is presented in this paper. The indoor environment is divided into several local maps, which are assumed to be independent of each other. The local areas are estimated by the local particle filter, whereas the global areas are com- bined by the global particle filter. The algorithm has been investigated by real field trials using a WiFi tablet on hand with an inertial sensor on foot. It could be concluded that the proposed method reduces the complexity of the positioning algorithm obviously, as well as offers a significant improvement in position accuracy compared to other conventional algorithms, allowing indoor positioning error below 1.2 m.展开更多
This paper addresses the challenge of accurately and timely determining the position of a train,with specific consideration given to the integration of the global navigation satellite system(GNSS)and inertial navigati...This paper addresses the challenge of accurately and timely determining the position of a train,with specific consideration given to the integration of the global navigation satellite system(GNSS)and inertial navigation system(INS).To overcome the increasing errors in the INS during interruptions in GNSS signals,as well as the uncertainty associated with process and measurement noise,a deep learning-based method for train positioning is proposed.This method combines convolutional neural networks(CNN),long short-term memory(LSTM),and the invariant extended Kalman filter(IEKF)to enhance the perception of train positions.It effectively handles GNSS signal interruptions and mitigates the impact of noise.Experimental evaluation and comparisons with existing approaches are provided to illustrate the effectiveness and robustness of the proposed method.展开更多
As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from bo...As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.展开更多
This paper proposes a novel indoor positioning scheme based on visible light communication(VLC).A new indoor VLC positioning scheme using fingerprint database with multi-parameters have been raised.We conduct simulati...This paper proposes a novel indoor positioning scheme based on visible light communication(VLC).A new indoor VLC positioning scheme using fingerprint database with multi-parameters have been raised.We conduct simulation and experimental research on the illumination intensity distribution of several direction parameters.In the experiment,four LED matrixes are identified by LED-ID with room dimensions of 3.75×4.00×2.7 m^3.The results show that the mean of the location error is 0.22 m in the receiving plane,verifying the correctness and feasibility of the positioning scheme.展开更多
Positive Q-value neutron transfer mediated sub-barrier fusion reactions are studied with an empirical coupled channels model, which takes into account neutron rearrangement related only to the dynamical matching condi...Positive Q-value neutron transfer mediated sub-barrier fusion reactions are studied with an empirical coupled channels model, which takes into account neutron rearrangement related only to the dynamical matching condition with no free parameters. Fusion cross sections of collision systems ^32S＋^90,94,96Zr are calculated and analyzed. Logarithmic residual enhancement （LRE） is proposed to evaluate the discrepancy between calculated results and experimental data. The experimental data can be described well with this model for the first time as a whole, while the LRE analysis shows that there are still theoretical systematic deviations.展开更多
To solve low precision and poor stability of the extended Kalman filter （EKF） in the vehicle integrated positioning system owing to acceleration, deceleration and turning （hereinafter referred to as maneuvering） ,...To solve low precision and poor stability of the extended Kalman filter （EKF） in the vehicle integrated positioning system owing to acceleration, deceleration and turning （hereinafter referred to as maneuvering） , the paper presents an adaptive filter algorithm that combines interacting multiple model （IMM） and non linear Kalman filter. The algorithm describes the motion mode of vehicle by using three state spacemode]s. At first, the parallel filter of each model is realized by using multiple nonlinear filters. Then the weight integration of filtering result is carried out by using the model matching likelihood function so as to get the system positioning information. The method has advantages of nonlinear system filter and overcomes disadvantages of single model of filtering algorithm that has poor effects on positioning the maneuvering target. At last, the paper uses IMM and EKF methods to simulate the global positioning system （OPS）/inertial navigation system （INS）/dead reckoning （DR） integrated positioning system, respectively. The results indicate that the IMM algorithm is obviously superior to EKF filter used in the integrated positioning system at present. Moreover, it can greatly enhance the stability and positioning precision of integrated positioning system.展开更多
Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP), one of the most important laboratories on magnetically confined fusion in China and the Nuclear Fusion Research Center of the World Laboratory, is sear...Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP), one of the most important laboratories on magnetically confined fusion in China and the Nuclear Fusion Research Center of the World Laboratory, is searching for 5 senior and 10 junior scientists of plasma and fusion in the following superconducting tokamak research areas: theory and simulation, diverter and edge physics, plasma diagnostics, electron cyclotron resonant heating, ion cyclotron resonant heating, lower hybrid wave, neutral beam injection, reactor design, fusion material, superconducting engineering.展开更多
Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP), one of the most important laboratories on magnetically confined fusion in China and the Nuclear Fusion Research Center of the World Laboratory, is sear...Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP), one of the most important laboratories on magnetically confined fusion in China and the Nuclear Fusion Research Center of the World Laboratory, is searching for 5 senior and 10 junior scientists of plasma and fusion in the following superconducting tokamak research areas: theory and simulation, diverter and edge physics, plasma diagnostics, electron cyclotron resonant heating, ion cyclotron resonant heating, lower hybrid wave, neutral beam injection, reactor design, fusion material, superconducting engineering.展开更多
Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP), one of the most important Laboratories on magnetically confined fusion in China and the Nuclear Fusion Research Center of the World Laboratory, is sear...Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP), one of the most important Laboratories on magnetically confined fusion in China and the Nuclear Fusion Research Center of the World Laboratory, is searching for 5 senior and 10 junior scientists of plasma and fusion in the following superconducting tokamak research areas: theory and simulation, diverter and edge physics, plasma diagnostics, electron cyclotron resonant heating, ion cyclotron resonant heating, lower hybrid wave, neutral beam injection, reactor design, fusion material, superconducting engineering.展开更多
The combination of Precision Point Positioning(PPP)with Multi-Global Navigation Satellite System(MultiGNSS),called MGPPP,can improve the positioning precision and shorten the convergence time more effectively than the...The combination of Precision Point Positioning(PPP)with Multi-Global Navigation Satellite System(MultiGNSS),called MGPPP,can improve the positioning precision and shorten the convergence time more effectively than the combination of PPP with only the BeiDou Navigation Satellite System(BDS).However,the Inter-System Bias(ISB)measurement of Multi-GNSS,including the time system offset,the coordinate system difference,and the inter-system hardware delay bias,must be considered for Multi-GNSS data fusion processing.The detected ISB can be well modeled and predicted by using a quadratic model(QM),an autoregressive integrated moving average model(ARIMA),as well as the sliding window strategy(SW).In this study,the experimental results indicate that there is no apparent difference in the ISB between BDS-2 and BDS-3 observations if B1I/B3I signals are used.However,an obvious difference in ISB can be found between BDS-2 and BDS-3 observations if B1I/B3I and B1C/B2a signals are used.Meanwhile,the precision of the Predicted ISB(PISB)on the next day of all stations is about 0.1−0.6 ns.Besides,to effectively utilize the PISB,a new strategy for predicting the PISB for MGPPP is proposed.In the proposed strategy,the PISB is used by adding two virtual observation equations,and an adaptive factor is adopted to balance the contribution of the Observed ISB(OISB)and the PISB to the final estimations of ISB.To validate the effectiveness of the proposed method,some experimental schemes are designed and tested under different satellite availability conditions.The results indicate that in open sky environment,the selective utilization of the PISB achieves almost the same positioning precision of MGPPP as the direct utilization of the PISB,but the convergence time of MGPPP is reduced by 7.1%at most in the north(N),east(E),and up(U)components.In the blocked sky environment,the selective utilization of the PISB contributes to more significant improvement of the positioning precision and convergence time than that in the open sky environment.Compared with the direct utilization of the PISB,the selective utilization of the PISB improves the positioning precision and convergence time by 6.7%and 12.7%at most in the N,E,and U components,respectively.展开更多
基金supported in part by the National Natural Science Foundation of China(Nos.62171375,62271397,62001392,62101458,62173276,61803310 and 61801394)the Shenzhen Science and Technology Innovation ProgramChina(No.JCYJ20220530161615033)。
文摘The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)denial conditions.Therefore,this paper proposes a UAV Clusters Information Geometry Fusion Positioning(UC-IGFP)method using pseudoranges from the LEO satellites.A novel graph model for linking and computing between the UAV clusters and LEO satellites was established.By utilizing probability to describe the positional states of UAVs and sensor errors,the distributed multivariate Probability Fusion Cooperative Positioning(PF-CP)algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster.Criteria to select the centroid of the cluster were set.A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory,which overcomes the discontinuity problem caused by the change of cluster centroids.Finally,the UC-IGFP method achieves the LEO continuous highprecision positioning of UAV clusters.The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster.It significantly improves the accuracy and reliability of LEO-UAV cluster positioning.The results of comprehensive simulation experiments show that the proposed method has a 30.5%improvement in performance over the mainstream positioning methods,with a positioning error of 14.267 m.
基金supported by the National Natural Science Foundation of China(6153102061471383)
文摘An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.
基金the National Natural Science Foundation of China(Grant No.42271436)the Shandong Provincial Natural Science Foundation,China(Grant Nos.ZR2021MD030,ZR2021QD148).
文摘The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic mismatch.In this study,a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed,where Wi-Fi,PDR,and geomagnetic signals are integrated to improve indoor positioning performances.One important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter algorithm.During the positioning process,an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range respectively.The position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected,which made up for the shortage of only one time of geomagnetic correction in the existing particle filter algorithm.In addition,this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving,which satisfies the real-time requirement of our fusion positioning approach.Through experimental verification,the average positioning accuracy of the proposed approach reaches 1.59 m,which improves 33.2%compared with the existing particle filter fusion positioning algorithms.
基金supported by the National tural Science Foundation of ChinaNa[grant number 41974038]NaThe tional Key Research and Development Program of China[grant number 2018YFC0809804].
文摘NaGlobal vigation Satellite System(GNSS)positioning technology is widely used for its high precision,global,and all-weather service.However,in complex environments such as urban canyons,GNSS performance is often degraded due to signal occlusion and even fails to achieve positioning due to the insufficient visible satellites.Because of the characteristics of large band-width,low latency,and high Base Station(BS)density,the fifth-Generation mobile communication(5G)technology has gradually become a trend for positioning in cities while offering traditional communication service.To supply the communication demands of the User Equipment(UE),only one BS is usually considered to establish a connection with the UE during the BS construction.However,the positioning accuracy with a single BS in urban canyons will be significantly reduced.To further improve the positioning accuracy in such extreme scenarios,this paper proposes a simplified 5G/GNSS fusion positioning system architecture using observations from only a 5G BS and a GNSS satellite.In this system,the GNSS receiver is mounted on the 5G BS,and the measurements provided by the receiver are used to form the differential code and complete the position estimation.The positioning mathematical models of the system based on the original code and differential code are derived.Then,the impacts of the measurements noise and the time synchronization error on the positioning accuracy are analyzed theoretically.Finally,the positioning performance is investigated by a set of simulation experiments.Numerical results show that under the existing 5G measurement noise and 2 m’s code measurement noise,the improvement of the differential code based fusion positioning compared with the 5G-only positioning is more than 32%,which is also about 6%higher than the original code based fusion positioning.Besides,this improvement is not affected by the time synchronization error between the BS and the GNSS satellite.
基金supported in part by National Natural Science Foundation of China(Nos.62073163,62103285,62203228)National Defense Basic Research Program(No.JCKY2020605C009)+1 种基金Aeronautic Science Foundation of China(Nos.ASFC-2020Z071052001,202055052003)Foundation Strengthening Program Technology 173 Field Fund(No.2021-JCJQ-JJ-0308)。
文摘In order to solve the problem of limited computational resources of multi-unmanned systems airborne navigation platform,a distributed cooperative positioning method based on confidence evaluation is proposed.Firstly,the impact of ranging error,priori information,spatial geometric configuration and adjacent nodes count on cooperative positioning performance are analyzed individually.Secondly,a confidence evaluation method for measurement information of adjacent nodes is designed according to the cooperative positioning principle,which comprehensively considers the coupling relationship between influencing factors.Finally,a distributed cooperative navigation filter based on inter-vehicle ranging is designed.Simulation studies show that confidence evaluation method proposed in this paper can effectively characterize the contribution of measurement information to positioning results,and positioning accuracy under the proposed method is improved by more than 15%compared with the traditional screening methods based on optimal geometric configuration and closest distance.
基金supported by the Collaborative Tackling Project of the Yangtze River Delta SciTech Innovation Community(Nos.2024CSJGG01503,2024CSJGG01500)Guangxi Key Research and Development Program(No.AB24010317)Jiangxi Provincial Key Laboratory of Electronic Data Control and Forensics(Jiangxi Police College)(No.2025JXJYKFJJ002).
文摘Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the varying importance of each modality across different contexts,a central and pressing challenge in multimodal sentiment analysis lies in maximizing the use of rich intra-modal features while minimizing information loss during the fusion process.In response to these critical limitations,we propose a novel framework that integrates spatial position encoding and fusion embedding modules to address these issues.In our model,text is treated as the core modality,while speech and video features are selectively incorporated through a unique position-aware fusion process.The spatial position encoding strategy preserves the internal structural information of speech and visual modalities,enabling the model to capture localized intra-modal dependencies that are often overlooked.This design enhances the richness and discriminative power of the fused representation,enabling more accurate and context-aware sentiment prediction.Finally,we conduct comprehensive evaluations on two widely recognized standard datasets in the field—CMU-MOSI and CMU-MOSEI to validate the performance of the proposed model.The experimental results demonstrate that our model exhibits good performance and effectiveness for sentiment analysis tasks.
基金the National Natural Science Foundation of China(Nos.61903249,61973215,and 62022055)the Shandong Key Research and Development Project(No.2019JZZY020131)。
文摘This study proposes a Kalman filter-based indoor vehicle positioning method for cases in which the steering angle and rotation speed of the vehicle’s wheels are unknown.By fusing the position and velocity data from the ultra-wideband sensors and acceleration and orientation data from the inertial measurement unit,we developed two algorithms to estimate the real-time position of the vehicle based on a linear Kalman filter and extended Kalman filter,respectively.We then conducted simulations and experiments to examine the performances of the algorithms.In the experiment,the Kalman filtering hyperparameters are configured,and we then ran the two algorithms to determine the positioning precision and accuracy with the ground truth produced via LiDAR.We verified that our method can improve precision and accuracy compared with the raw positioning data and can achieve desirable effects for indoor vehicle positioning when vehicles travel at low speeds.
基金The National Natural Science Foundation of China(No. 40804015,61101163)
文摘An efficient vehicle detection approach is proposed for traffic surveillance images, which is based on information fusion of vehicle symmetrical contour and license plate position. The vertical symmetry axis of the vehicle contour in an image is. first detected, and then the vertical and the horizontal symmetry axes of the license plate are detected using the symmetry axis of the vehicle contour as a reference. The vehicle location in an image is determined using license plate symmetry axes and the vertical and the horizontal projection maps of the vehicle edge image. A dataset consisting of 450 images （15 classes of vehicles） is used to test the proposed method. The experimental results indicate that compared with the vehicle contour-based, the license plate location-based, the vehicle texture-based and the Gabor feature-based methods, the proposed method is the best with a detection accuracy of 90.7% and an elapsed time of 125 ms.
文摘WiFi fingerprinting is the method of recording WiFi signal strength from access points （AP） along with the positions at which they were recorded, and later matching those to new mea- surements for indoor positioning. Inertial positioning utilizes the accelerometer and gyroscopes for pedestrian positioning. However, both methods have their limitations, such as the WiFi fluctuations and the accumulative error of inertial sensors. Usually, the filtering method is used for integrating the two approaches to achieve better location accuracy. In the real environments, especially in the indoor field, the APs could be sparse and short range. To overcome the limitations, a novel particle filter approach based on Rao Blackwellized particle filter （RBPF） is presented in this paper. The indoor environment is divided into several local maps, which are assumed to be independent of each other. The local areas are estimated by the local particle filter, whereas the global areas are com- bined by the global particle filter. The algorithm has been investigated by real field trials using a WiFi tablet on hand with an inertial sensor on foot. It could be concluded that the proposed method reduces the complexity of the positioning algorithm obviously, as well as offers a significant improvement in position accuracy compared to other conventional algorithms, allowing indoor positioning error below 1.2 m.
基金supported by the National Natural Science Foundation of China(Nos.61925302,62273027)the Beijing Natural Science Foundation(L211021).
文摘This paper addresses the challenge of accurately and timely determining the position of a train,with specific consideration given to the integration of the global navigation satellite system(GNSS)and inertial navigation system(INS).To overcome the increasing errors in the INS during interruptions in GNSS signals,as well as the uncertainty associated with process and measurement noise,a deep learning-based method for train positioning is proposed.This method combines convolutional neural networks(CNN),long short-term memory(LSTM),and the invariant extended Kalman filter(IEKF)to enhance the perception of train positions.It effectively handles GNSS signal interruptions and mitigates the impact of noise.Experimental evaluation and comparisons with existing approaches are provided to illustrate the effectiveness and robustness of the proposed method.
基金National Natural Science Foundation of China(Grant No.62101138)Shandong Natural Science Foundation(Grant No.ZR2021QD148)+1 种基金Guangdong Natural Science Foundation(Grant No.2022A1515012573)Guangzhou Basic and Applied Basic Research Project(Grant No.202102020701)for providing funds for publishing this paper。
文摘As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.
基金supported by ZTE Industry-Academia-Research Cooperation Funds under Grant No.2014ZTE02-12
文摘This paper proposes a novel indoor positioning scheme based on visible light communication(VLC).A new indoor VLC positioning scheme using fingerprint database with multi-parameters have been raised.We conduct simulation and experimental research on the illumination intensity distribution of several direction parameters.In the experiment,four LED matrixes are identified by LED-ID with room dimensions of 3.75×4.00×2.7 m^3.The results show that the mean of the location error is 0.22 m in the receiving plane,verifying the correctness and feasibility of the positioning scheme.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11635003,11025524,11161130520,11175218and U1332207the National Basic Research Program of China under Grant No 2010CB832903the European Commission's 7th Framework Programme(Fp7-PEOPLE-2010-IRSES)under Grant No 269131
文摘Positive Q-value neutron transfer mediated sub-barrier fusion reactions are studied with an empirical coupled channels model, which takes into account neutron rearrangement related only to the dynamical matching condition with no free parameters. Fusion cross sections of collision systems ^32S＋^90,94,96Zr are calculated and analyzed. Logarithmic residual enhancement （LRE） is proposed to evaluate the discrepancy between calculated results and experimental data. The experimental data can be described well with this model for the first time as a whole, while the LRE analysis shows that there are still theoretical systematic deviations.
基金National Natural Science Foundation of China(No.61663020)Project of Education Department of Gansu Province(No.2016B-036)
文摘To solve low precision and poor stability of the extended Kalman filter （EKF） in the vehicle integrated positioning system owing to acceleration, deceleration and turning （hereinafter referred to as maneuvering） , the paper presents an adaptive filter algorithm that combines interacting multiple model （IMM） and non linear Kalman filter. The algorithm describes the motion mode of vehicle by using three state spacemode]s. At first, the parallel filter of each model is realized by using multiple nonlinear filters. Then the weight integration of filtering result is carried out by using the model matching likelihood function so as to get the system positioning information. The method has advantages of nonlinear system filter and overcomes disadvantages of single model of filtering algorithm that has poor effects on positioning the maneuvering target. At last, the paper uses IMM and EKF methods to simulate the global positioning system （OPS）/inertial navigation system （INS）/dead reckoning （DR） integrated positioning system, respectively. The results indicate that the IMM algorithm is obviously superior to EKF filter used in the integrated positioning system at present. Moreover, it can greatly enhance the stability and positioning precision of integrated positioning system.
文摘Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP), one of the most important laboratories on magnetically confined fusion in China and the Nuclear Fusion Research Center of the World Laboratory, is searching for 5 senior and 10 junior scientists of plasma and fusion in the following superconducting tokamak research areas: theory and simulation, diverter and edge physics, plasma diagnostics, electron cyclotron resonant heating, ion cyclotron resonant heating, lower hybrid wave, neutral beam injection, reactor design, fusion material, superconducting engineering.
文摘Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP), one of the most important laboratories on magnetically confined fusion in China and the Nuclear Fusion Research Center of the World Laboratory, is searching for 5 senior and 10 junior scientists of plasma and fusion in the following superconducting tokamak research areas: theory and simulation, diverter and edge physics, plasma diagnostics, electron cyclotron resonant heating, ion cyclotron resonant heating, lower hybrid wave, neutral beam injection, reactor design, fusion material, superconducting engineering.
文摘Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP), one of the most important Laboratories on magnetically confined fusion in China and the Nuclear Fusion Research Center of the World Laboratory, is searching for 5 senior and 10 junior scientists of plasma and fusion in the following superconducting tokamak research areas: theory and simulation, diverter and edge physics, plasma diagnostics, electron cyclotron resonant heating, ion cyclotron resonant heating, lower hybrid wave, neutral beam injection, reactor design, fusion material, superconducting engineering.
基金supported by“The National Key Research and Development Program of China(No.2020YFA0713502)”“The National Natural Science Foundation of China(No.41874039)”+1 种基金“Jiangsu National Science Foundation(No.BK20191342)”“Fundamental Research Funds for the Central Universities(No.2019ZDPY-RH03)”。
文摘The combination of Precision Point Positioning(PPP)with Multi-Global Navigation Satellite System(MultiGNSS),called MGPPP,can improve the positioning precision and shorten the convergence time more effectively than the combination of PPP with only the BeiDou Navigation Satellite System(BDS).However,the Inter-System Bias(ISB)measurement of Multi-GNSS,including the time system offset,the coordinate system difference,and the inter-system hardware delay bias,must be considered for Multi-GNSS data fusion processing.The detected ISB can be well modeled and predicted by using a quadratic model(QM),an autoregressive integrated moving average model(ARIMA),as well as the sliding window strategy(SW).In this study,the experimental results indicate that there is no apparent difference in the ISB between BDS-2 and BDS-3 observations if B1I/B3I signals are used.However,an obvious difference in ISB can be found between BDS-2 and BDS-3 observations if B1I/B3I and B1C/B2a signals are used.Meanwhile,the precision of the Predicted ISB(PISB)on the next day of all stations is about 0.1−0.6 ns.Besides,to effectively utilize the PISB,a new strategy for predicting the PISB for MGPPP is proposed.In the proposed strategy,the PISB is used by adding two virtual observation equations,and an adaptive factor is adopted to balance the contribution of the Observed ISB(OISB)and the PISB to the final estimations of ISB.To validate the effectiveness of the proposed method,some experimental schemes are designed and tested under different satellite availability conditions.The results indicate that in open sky environment,the selective utilization of the PISB achieves almost the same positioning precision of MGPPP as the direct utilization of the PISB,but the convergence time of MGPPP is reduced by 7.1%at most in the north(N),east(E),and up(U)components.In the blocked sky environment,the selective utilization of the PISB contributes to more significant improvement of the positioning precision and convergence time than that in the open sky environment.Compared with the direct utilization of the PISB,the selective utilization of the PISB improves the positioning precision and convergence time by 6.7%and 12.7%at most in the N,E,and U components,respectively.
