To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference a...To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference and external malicious jamming. A cooperative anti-jamming and interference mitigation method based on local altruistic is proposed to optimize UAVs’ channel selection. Specifically, a Stackelberg game is modeled to formulate the confrontation relationship between UAVs and the jammer. A local altruistic game is modeled with each UAV considering the utilities of both itself and other UAVs. A distributed cooperative anti-jamming and interference mitigation algorithm is proposed to obtain the Stackelberg equilibrium. Finally, the convergence of the proposed algorithm and the impact of the transmission power on the system loss value are analyzed, and the anti-jamming performance of the proposed algorithm can be improved by around 64% compared with the existing algorithms.展开更多
In anchor-free environments,where no devices with known positions are available,the error growth of autonomous underwater vehicle(AUV)localization and target tracking is unbounded due to the lack of references and the...In anchor-free environments,where no devices with known positions are available,the error growth of autonomous underwater vehicle(AUV)localization and target tracking is unbounded due to the lack of references and the accumulated errors in inertial measurements.This paper aims to improve the localization and tracking accuracy by involving current information as extra references.We first integrate current measurements and maps with belief propagation and design a distributed current-aided message-passing scheme that theoretically solves the localization and tracking problems.Based on this scheme,we propose particle-based cooperative localization and target tracking algorithms,named CaCL and CaTT,respectively.In AUV localization,CaCL uses the current measurements to correct the predicted and transmitted position information and alleviates the impact of the accumulated errors in inertial measurements.With target tracking,the current maps are applied in CaTT to modify the position prediction of the target which is calculated through historical estimates.The effectiveness and robustness of the proposed methods are validated through various simulations by comparisons with alternative methods under different trajectories and current conditions.展开更多
A challenging issue in intelligent transportation systems (ITS) is to accurately locate moving vehicles in urban area. Considerable ef- forts have been made to improve the localization accuracy of standalone GPS rec...A challenging issue in intelligent transportation systems (ITS) is to accurately locate moving vehicles in urban area. Considerable ef- forts have been made to improve the localization accuracy of standalone GPS receivers. However, through empirical study, we found that the latitude and longitude values generated by GPS receivers fluctuate significantly because of the muhipath effect in urban ar- eas. The relative distances between neighboring vehicles with similar GPS signal data in terms of satellite sets and signal strength are much more stable in such a scenario. In this paper, we propose a cooperative localization algorithm, Networking-GPS, to improve the accuracy of location information for vehicular networks in urban area using commodity GPS receivers. First, atom redundantly rigid graphs of vehicles are constructed according to the similarity of neighboring GPS data. Then, through rigidity expansion, local accura- cy can enforce global accuracy. Extensive simulations based on the real road network and trace data of vehicle mobility demonstrate that Networking-GPS can improve the accuracy of the entire system.展开更多
The global navigation satellite system(GNSS)is currently being used extensively in the navigation system of vehicles.However,the GNSS signal will be faded or blocked in complex road environments,which will lead to a d...The global navigation satellite system(GNSS)is currently being used extensively in the navigation system of vehicles.However,the GNSS signal will be faded or blocked in complex road environments,which will lead to a decrease in positioning accuracy.Owing to the higher-precision synchronization provided in the sixth generation(6G)network,the errors of ranging-based positioning technologies can be effectively reduced.At the same time,the use of terahertz in 6G allows excellent resolution of range and angle,which offers unique opportunities for multi-vehicle cooperative localization in a GNSS denied environment.This paper introduces a multi-vehicle cooperative localization method.In the proposed method,the location estimations of vehicles are derived by utilizing inertial measurement and then corrected by exchanging the beliefs with adjacent vehicles and roadside units.The multi-vehicle cooperative localization problem is represented using a factor graph.An iterative algorithm based on belief propagation is applied to perform the inference over the factor graph.The results demonstrate that our proposed method can offer a considerable capability enhancement on localization accuracy.展开更多
Based on multiple unmanned aerial vehicles(UAVs) flight at a constant altitude,a fault-tolerant cooperative localization algorithm against global positioning system(GPS) signal loss due to GPS receiver malfunction...Based on multiple unmanned aerial vehicles(UAVs) flight at a constant altitude,a fault-tolerant cooperative localization algorithm against global positioning system(GPS) signal loss due to GPS receiver malfunction is proposed.Contrast to the traditional means with single UAV,the proposed method is based on the use of inter-UAV relative range measurements against GPS signal loss and more suitable for the small-size and low-cost UAV applications.Firstly,for re-localizing an UAV with a malfunction in its GPS receiver,an algorithm which makes use of any other three healthy UAVs in the cooperative flight as the reference points for re-localization is proposed.Secondly,by using the relative ranges from the faulty UAV to the other three UAVs,its horizontal location can be determined after the GPS signal is lost.In order to improve an accuracy of the localization,a Kalman filter is further exploited to provide the estimated location of the UAV with the GPS signal loss.The Kalman filter calculates the variance of observations in terms of horizontal dilution of positioning(HDOP) automatically.Then,during each discrete computing time step,the best reference points are selected adaptively by minimizing the HDOP.Finally,two simulation examples in Matlab/Simulink environment with five UAVs in cooperative flight are shown to evaluate the effectiveness of the proposed method.展开更多
The cooperative localization(CL)is affected by the communication topology among the platforms.Based on the unscented Kalman filtering,the distributed CL(DCL)oriented to the unpredicted communication topology is invest...The cooperative localization(CL)is affected by the communication topology among the platforms.Based on the unscented Kalman filtering,the distributed CL(DCL)oriented to the unpredicted communication topology is investigated.To improve the adaptability,the character of the look-up Cholesky decomposition is exploited for the covariance matrix decomposing.Then,the distributed U transformation can be dynamically implemented according to the available communication topology.In the proposed algorithm,the global information is not required for the individual,and only the available information from the neighbor is used.Each platform’s state can be estimated independently.The error covariance of the state estimates can be updated in the single platform.The algorithm is adaptive to any serial communication topologies where the measuring to the measured platform is a starting path.The applicability of the proposed algorithm to unpredicted communication topology is improved,remaining equivalent localization performance to free connection communication.展开更多
In cooperative localization with sparse communication networks, an agent maybe only receives part of locating messages from the others. It is difficult for the receiver to utilize the part instead of global knowledge....In cooperative localization with sparse communication networks, an agent maybe only receives part of locating messages from the others. It is difficult for the receiver to utilize the part instead of global knowledge. Under the extended Kalman filtering, the utilization of the locating message is maximized by two aspects: the locating message generating and multi-locating messages fusing. For the former, the covariance upper-bound technique, by introducing amplification coefficients, is employed to remove the dependency of locating messages on the global knowledge. For the latter, an optimization model is setup; the covariance matrix determinant of the receiver's state estimate, expressed as a function of the amplification coefficients, is selected as the optimization criterion, under linear constraints on the amplification coefficient characteristics and the communication connectivity. Using the optimization solution, the local optimal state of the receiver agent is obtained by the weighting fusion. Simulation with seven agents is shown to evaluate the effectiveness of the proposed algorithm.展开更多
With the rapid development of educational reform and innovation,Sino-foreign Cooperative Institutions have made greatachievements.Especially after China entered the WTO,as foreign universities educational resources ar...With the rapid development of educational reform and innovation,Sino-foreign Cooperative Institutions have made greatachievements.Especially after China entered the WTO,as foreign universities educational resources are introduced,the localiza-tion of English language teaching arouse much attention.This paper is to explore and study the Localization of English LanguageTeaching at Sino-foreign Cooperative Institutions.And then is the study on localization of English language teaching at SIAS Inter-national University.Through the evidence of this paper shows,it can pose a theory reference and support to Sino-foreign Coopera-tive Institutions.展开更多
In order to maximize the utilization of the observation information in the cooperative localization,a compensation algorithm based on the estimation state is presented for transmission delay.Under the framework of the...In order to maximize the utilization of the observation information in the cooperative localization,a compensation algorithm based on the estimation state is presented for transmission delay.Under the framework of the Kalman filter,two different processes of state estimating with and without transmission delay are investigated and contrasted.The expression of difference quantity caused by transmission delay is derived.It is used to compensate the present estimation state instead of the observed information compensation.According to the characteristics of state transition matrix,an equivalent expression of which successively impacts on the covariance factor in delay time is obtained.The simulation results show that the present estimated state is effectively corrected by transmission information and the relevance among agents is accurately updated.As a result,a higher positioning accuracy is achieved.Meanwhile,the consumption of recording and multiplication of the state transition matrix is saved.展开更多
The underwater wireless sensor network(UWSN) has the features of mobility by drifting,less beacon nodes,longer time for localization and more energy consumption than the terrestrial sensor networks,which makes it more...The underwater wireless sensor network(UWSN) has the features of mobility by drifting,less beacon nodes,longer time for localization and more energy consumption than the terrestrial sensor networks,which makes it more difficult to locate the nodes in marine environment.Aiming at the characteristics of UWSN,a kind of cooperative range-free localization method based on weighted centroid localization(WCL) algorithm for three-dimensional UWSN is proposed.The algorithm assigns the cooperative weights for the beacon nodes according to the received acoustic signal strength,and uses the located unknown nodes as the new beacon nodes to locate the other unknown nodes,so a fast localization can be achieved for the whole sensor networks.Simulation results indicate this method has higher localization accuracy than the centroid localization algorithm,and it needs less beacon nodes and achieves higher rate of effective localization.展开更多
In recent years,position information has become a key feature to drive location and context aware services in mobile communication.Researchers from all over the world have proposed many solu-tions for indoor positioni...In recent years,position information has become a key feature to drive location and context aware services in mobile communication.Researchers from all over the world have proposed many solu-tions for indoor positioning over the past several years.However,due to weak signals,multipath or non-line-of-sight signal propagation,accurately and efficiently localizing targets in harsh indoor environments re-mains a challenging problem.To improve the perfor-mance in harsh environment with insufficient anchors,cooperative localization has emerged.In this paper,a novel cooperative localization algorithm,named area optimization and node selection based sum-product al-gorithm over a wireless network(AN-SPAWN),is de-scribed and analyzed.To alleviate the high compu-tational complexity and build optimized cooperative cluster,a node selection method is designed for the cooperative localization algorithm.Numerical experi-ment results indicate that our proposed algorithm has a higher accuracy and is less impacted by NLOS errors than other conventional cooperative localization algo-rithms in the harsh indoor environments.展开更多
Wind energy has been widely applied in power generation to alleviate climate problems.The wind turbine layout of a wind farm is a primary factor of impacting power conversion efficiency due to the wake effect that red...Wind energy has been widely applied in power generation to alleviate climate problems.The wind turbine layout of a wind farm is a primary factor of impacting power conversion efficiency due to the wake effect that reduces the power outputs of wind turbines located in downstream.Wind farm layout optimization(WFLO)aims to reduce the wake effect for maximizing the power outputs of the wind farm.Nevertheless,the wake effect among wind turbines increases significantly as the number of wind turbines increases in the wind farm,which severely affect power conversion efficiency.Conventional heuristic algorithms suffer from issues of low solution quality and local optimum for large-scale WFLO under complex wind scenarios.Thus,a chaotic local search-based genetic learning particle swarm optimizer(CGPSO)is proposed to optimize large-scale WFLO problems.CGPSO is tested on four larger-scale wind farms under four complex wind scenarios and compares with eight state-of-the-art algorithms.The experiment results indicate that CGPSO significantly outperforms its competitors in terms of performance,stability,and robustness.To be specific,a success and failure memories-based selection is proposed to choose a chaotic map for chaotic search local.It improves the solution quality.The parameter and search pattern of chaotic local search are also analyzed for WFLO problems.展开更多
For situations such as indoor and underground parking lots in which satellite signals are obstructed,GNSS cooperative positioning can be used to achieve highprecision positioning with the assistance of cooperative nod...For situations such as indoor and underground parking lots in which satellite signals are obstructed,GNSS cooperative positioning can be used to achieve highprecision positioning with the assistance of cooperative nodes.Here we study the cooperative positioning of two static nodes,node 1 is placed on the roof of the building and the satellite observation is ideal,node 2 is placed on the indoor windowsill where the occlusion situation is more serious,we mainly study how to locate node 2 with the assistance of node 1.Firstly,the two cooperative nodes are located with pseudo-range single point positioning,and the positioning performance of cooperative node is analyzed,therefore the information of pseudo-range and position of node 1 is obtained.Secondly,the distance between cooperative nodes is obtained by using the baseline method with double-difference carrier phase.Finally,the cooperative location algorithms are studied.The Extended Kalman Filtering(EKF),Unscented Kalman Filtering(UKF)and Particle Filtering(PF)are used to fuse the pseudo-range,ranging information and location information respectively.Due to the mutual influences among the cooperative nodes in cooperative positioning,the EKF,UKF and PF algorithms are improved by resetting the error covariance matrix of the cooperative nodes at each update time.Experimental results show that after being improved,the influence between the cooperative nodes becomes smaller,and the positioning performance of the nodes is better than before.展开更多
Cooperative learning emerging as the leading new approach to classroom instruction abroad over the past decades has been studied by many researchers from all aspects.This paper mainly focuses on the basics of cooperat...Cooperative learning emerging as the leading new approach to classroom instruction abroad over the past decades has been studied by many researchers from all aspects.This paper mainly focuses on the basics of cooperative learning and tries to answer the question that if the use of cooperative learning produce higher achievement than the traditional methods in college English reading class through experimental study.The analysis contributes to better college English teaching and learning.A conclusion is drawn that cooperative learning is very effective in improving college students reading ability.展开更多
This paper provides theoretical foundation tor the problem ot localization in multi-robot formations. Sufficient and necessary conditions for completely localizing a formation of mobile robots/vehicles in SE(2) based ...This paper provides theoretical foundation tor the problem ot localization in multi-robot formations. Sufficient and necessary conditions for completely localizing a formation of mobile robots/vehicles in SE(2) based on distributed sensor networks and graph rigidity are proposed. A method for estimating the quality of localizations via a linearized weighted least-squares algorithm is presented, which considers incomplete and noisy sensory information. The approach in this paper had been implemented in a multi-robot system of five car-like robots equipped with omni-directional cameras and IEEE 802.11b wireless network.展开更多
At present, there are many effective ways to achieve high performance in cluster system storage management, including server-end disk, server-end caching, local caching and cooperative caching. The cooperative caching...At present, there are many effective ways to achieve high performance in cluster system storage management, including server-end disk, server-end caching, local caching and cooperative caching. The cooperative caching mechanism shares caches among different clients so as to avoid expensive disk access costs and to improve overall throughput of cluster system. In this paper, a Single Copy Cooperative Cache model is proposed together with block lookup algorithm, block replacement algorithm and the consistency algorithm based on the model. Meanwhile, the prototype system of the model is implemented in PVFS file system. Finally, the performance of this system is tested in InfiniBand Framework, the result of which shows that in contrast to the original PVFS system, read performance of PVFS file system is improved by about two times, while write performance is reduced by nearly ten percent.展开更多
基金supported in part by the National Natural Science Foundation of China (No.62271253,61901523,62001381)Fundamental Research Funds for the Central Universities (No.NS2023018)+2 种基金the National Aerospace Science Foundation of China under Grant 2023Z021052002the open research fund of National Mobile Communications Research Laboratory,Southeast University (No.2023D09)Postgraduate Research & Practice Innovation Program of NUAA (No.xcxjh20220402)。
文摘To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference and external malicious jamming. A cooperative anti-jamming and interference mitigation method based on local altruistic is proposed to optimize UAVs’ channel selection. Specifically, a Stackelberg game is modeled to formulate the confrontation relationship between UAVs and the jammer. A local altruistic game is modeled with each UAV considering the utilities of both itself and other UAVs. A distributed cooperative anti-jamming and interference mitigation algorithm is proposed to obtain the Stackelberg equilibrium. Finally, the convergence of the proposed algorithm and the impact of the transmission power on the system loss value are analyzed, and the anti-jamming performance of the proposed algorithm can be improved by around 64% compared with the existing algorithms.
基金supported in part by the National Natural Science Foundation of China(62203299,61773264,61922058,61803261,61801295)the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University(SL2020ZD206,SL2020MS010,SL2020MS015)。
文摘In anchor-free environments,where no devices with known positions are available,the error growth of autonomous underwater vehicle(AUV)localization and target tracking is unbounded due to the lack of references and the accumulated errors in inertial measurements.This paper aims to improve the localization and tracking accuracy by involving current information as extra references.We first integrate current measurements and maps with belief propagation and design a distributed current-aided message-passing scheme that theoretically solves the localization and tracking problems.Based on this scheme,we propose particle-based cooperative localization and target tracking algorithms,named CaCL and CaTT,respectively.In AUV localization,CaCL uses the current measurements to correct the predicted and transmitted position information and alleviates the impact of the accumulated errors in inertial measurements.With target tracking,the current maps are applied in CaTT to modify the position prediction of the target which is calculated through historical estimates.The effectiveness and robustness of the proposed methods are validated through various simulations by comparisons with alternative methods under different trajectories and current conditions.
基金Supported by National High Technology Research and Development Program of China (863 Program) (2007AA809502C) National Natural Science Foundation of China (50979093) Program for New Century Excellent Talents in University (NCET-06-0877)
文摘A challenging issue in intelligent transportation systems (ITS) is to accurately locate moving vehicles in urban area. Considerable ef- forts have been made to improve the localization accuracy of standalone GPS receivers. However, through empirical study, we found that the latitude and longitude values generated by GPS receivers fluctuate significantly because of the muhipath effect in urban ar- eas. The relative distances between neighboring vehicles with similar GPS signal data in terms of satellite sets and signal strength are much more stable in such a scenario. In this paper, we propose a cooperative localization algorithm, Networking-GPS, to improve the accuracy of location information for vehicular networks in urban area using commodity GPS receivers. First, atom redundantly rigid graphs of vehicles are constructed according to the similarity of neighboring GPS data. Then, through rigidity expansion, local accura- cy can enforce global accuracy. Extensive simulations based on the real road network and trace data of vehicle mobility demonstrate that Networking-GPS can improve the accuracy of the entire system.
基金supported by the National Natural Science Foundation of China(No.61701020)the Scientific and Technological Innovation Foundation of Shunde Graduate School,USTB(No.BK19BF009)。
文摘The global navigation satellite system(GNSS)is currently being used extensively in the navigation system of vehicles.However,the GNSS signal will be faded or blocked in complex road environments,which will lead to a decrease in positioning accuracy.Owing to the higher-precision synchronization provided in the sixth generation(6G)network,the errors of ranging-based positioning technologies can be effectively reduced.At the same time,the use of terahertz in 6G allows excellent resolution of range and angle,which offers unique opportunities for multi-vehicle cooperative localization in a GNSS denied environment.This paper introduces a multi-vehicle cooperative localization method.In the proposed method,the location estimations of vehicles are derived by utilizing inertial measurement and then corrected by exchanging the beliefs with adjacent vehicles and roadside units.The multi-vehicle cooperative localization problem is represented using a factor graph.An iterative algorithm based on belief propagation is applied to perform the inference over the factor graph.The results demonstrate that our proposed method can offer a considerable capability enhancement on localization accuracy.
基金supported by the National Natural Science Foundation of China(60974146)the Natural Science and Engineering Research Council of Canada(NSERC)
文摘Based on multiple unmanned aerial vehicles(UAVs) flight at a constant altitude,a fault-tolerant cooperative localization algorithm against global positioning system(GPS) signal loss due to GPS receiver malfunction is proposed.Contrast to the traditional means with single UAV,the proposed method is based on the use of inter-UAV relative range measurements against GPS signal loss and more suitable for the small-size and low-cost UAV applications.Firstly,for re-localizing an UAV with a malfunction in its GPS receiver,an algorithm which makes use of any other three healthy UAVs in the cooperative flight as the reference points for re-localization is proposed.Secondly,by using the relative ranges from the faulty UAV to the other three UAVs,its horizontal location can be determined after the GPS signal is lost.In order to improve an accuracy of the localization,a Kalman filter is further exploited to provide the estimated location of the UAV with the GPS signal loss.The Kalman filter calculates the variance of observations in terms of horizontal dilution of positioning(HDOP) automatically.Then,during each discrete computing time step,the best reference points are selected adaptively by minimizing the HDOP.Finally,two simulation examples in Matlab/Simulink environment with five UAVs in cooperative flight are shown to evaluate the effectiveness of the proposed method.
文摘The cooperative localization(CL)is affected by the communication topology among the platforms.Based on the unscented Kalman filtering,the distributed CL(DCL)oriented to the unpredicted communication topology is investigated.To improve the adaptability,the character of the look-up Cholesky decomposition is exploited for the covariance matrix decomposing.Then,the distributed U transformation can be dynamically implemented according to the available communication topology.In the proposed algorithm,the global information is not required for the individual,and only the available information from the neighbor is used.Each platform’s state can be estimated independently.The error covariance of the state estimates can be updated in the single platform.The algorithm is adaptive to any serial communication topologies where the measuring to the measured platform is a starting path.The applicability of the proposed algorithm to unpredicted communication topology is improved,remaining equivalent localization performance to free connection communication.
基金supported by the National Natural Science Foundation of China(61273357)
文摘In cooperative localization with sparse communication networks, an agent maybe only receives part of locating messages from the others. It is difficult for the receiver to utilize the part instead of global knowledge. Under the extended Kalman filtering, the utilization of the locating message is maximized by two aspects: the locating message generating and multi-locating messages fusing. For the former, the covariance upper-bound technique, by introducing amplification coefficients, is employed to remove the dependency of locating messages on the global knowledge. For the latter, an optimization model is setup; the covariance matrix determinant of the receiver's state estimate, expressed as a function of the amplification coefficients, is selected as the optimization criterion, under linear constraints on the amplification coefficient characteristics and the communication connectivity. Using the optimization solution, the local optimal state of the receiver agent is obtained by the weighting fusion. Simulation with seven agents is shown to evaluate the effectiveness of the proposed algorithm.
文摘With the rapid development of educational reform and innovation,Sino-foreign Cooperative Institutions have made greatachievements.Especially after China entered the WTO,as foreign universities educational resources are introduced,the localiza-tion of English language teaching arouse much attention.This paper is to explore and study the Localization of English LanguageTeaching at Sino-foreign Cooperative Institutions.And then is the study on localization of English language teaching at SIAS Inter-national University.Through the evidence of this paper shows,it can pose a theory reference and support to Sino-foreign Coopera-tive Institutions.
基金Supported by the National Basic Research Program of China(2010CB731800)
文摘In order to maximize the utilization of the observation information in the cooperative localization,a compensation algorithm based on the estimation state is presented for transmission delay.Under the framework of the Kalman filter,two different processes of state estimating with and without transmission delay are investigated and contrasted.The expression of difference quantity caused by transmission delay is derived.It is used to compensate the present estimation state instead of the observed information compensation.According to the characteristics of state transition matrix,an equivalent expression of which successively impacts on the covariance factor in delay time is obtained.The simulation results show that the present estimated state is effectively corrected by transmission information and the relevance among agents is accurately updated.As a result,a higher positioning accuracy is achieved.Meanwhile,the consumption of recording and multiplication of the state transition matrix is saved.
基金National Nature Science Foundation of China(No.61273068)International Exchanges and Cooperation Projects of Shanghai Science and Technology Committee,China(No.15220721800)
文摘The underwater wireless sensor network(UWSN) has the features of mobility by drifting,less beacon nodes,longer time for localization and more energy consumption than the terrestrial sensor networks,which makes it more difficult to locate the nodes in marine environment.Aiming at the characteristics of UWSN,a kind of cooperative range-free localization method based on weighted centroid localization(WCL) algorithm for three-dimensional UWSN is proposed.The algorithm assigns the cooperative weights for the beacon nodes according to the received acoustic signal strength,and uses the located unknown nodes as the new beacon nodes to locate the other unknown nodes,so a fast localization can be achieved for the whole sensor networks.Simulation results indicate this method has higher localization accuracy than the centroid localization algorithm,and it needs less beacon nodes and achieves higher rate of effective localization.
基金the Nation-alKey Research&Development Program of China un-der Grant No.2020YFC1511702 and Open Fund of IPOC(BUPT)No.IPOC2021ZT20.
文摘In recent years,position information has become a key feature to drive location and context aware services in mobile communication.Researchers from all over the world have proposed many solu-tions for indoor positioning over the past several years.However,due to weak signals,multipath or non-line-of-sight signal propagation,accurately and efficiently localizing targets in harsh indoor environments re-mains a challenging problem.To improve the perfor-mance in harsh environment with insufficient anchors,cooperative localization has emerged.In this paper,a novel cooperative localization algorithm,named area optimization and node selection based sum-product al-gorithm over a wireless network(AN-SPAWN),is de-scribed and analyzed.To alleviate the high compu-tational complexity and build optimized cooperative cluster,a node selection method is designed for the cooperative localization algorithm.Numerical experi-ment results indicate that our proposed algorithm has a higher accuracy and is less impacted by NLOS errors than other conventional cooperative localization algo-rithms in the harsh indoor environments.
基金partially supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI(JP22H03643)Japan Science and Technology Agency(JST)Support for Pioneering Research Initiated by the Next Generation(SPRING)(JPMJSP2145)JST through the Establishment of University Fellowships towards the Creation of Science Technology Innovation(JPMJFS2115)。
文摘Wind energy has been widely applied in power generation to alleviate climate problems.The wind turbine layout of a wind farm is a primary factor of impacting power conversion efficiency due to the wake effect that reduces the power outputs of wind turbines located in downstream.Wind farm layout optimization(WFLO)aims to reduce the wake effect for maximizing the power outputs of the wind farm.Nevertheless,the wake effect among wind turbines increases significantly as the number of wind turbines increases in the wind farm,which severely affect power conversion efficiency.Conventional heuristic algorithms suffer from issues of low solution quality and local optimum for large-scale WFLO under complex wind scenarios.Thus,a chaotic local search-based genetic learning particle swarm optimizer(CGPSO)is proposed to optimize large-scale WFLO problems.CGPSO is tested on four larger-scale wind farms under four complex wind scenarios and compares with eight state-of-the-art algorithms.The experiment results indicate that CGPSO significantly outperforms its competitors in terms of performance,stability,and robustness.To be specific,a success and failure memories-based selection is proposed to choose a chaotic map for chaotic search local.It improves the solution quality.The parameter and search pattern of chaotic local search are also analyzed for WFLO problems.
基金This work was financially supported by National Major SpecialScience and Technology (No. GFZX0301040115)the National Natural Science Foundationof China (No. 61301094, No. 61571188)the Construct Program of the Key Discipline inHunan Province, China, the Aid program for Science and Technology Innovative ResearchTeam in Higher Educational Institute of Hunan Province, and the Planned Science andTechnology Project of Loudi City, Hunan Province, China.
文摘For situations such as indoor and underground parking lots in which satellite signals are obstructed,GNSS cooperative positioning can be used to achieve highprecision positioning with the assistance of cooperative nodes.Here we study the cooperative positioning of two static nodes,node 1 is placed on the roof of the building and the satellite observation is ideal,node 2 is placed on the indoor windowsill where the occlusion situation is more serious,we mainly study how to locate node 2 with the assistance of node 1.Firstly,the two cooperative nodes are located with pseudo-range single point positioning,and the positioning performance of cooperative node is analyzed,therefore the information of pseudo-range and position of node 1 is obtained.Secondly,the distance between cooperative nodes is obtained by using the baseline method with double-difference carrier phase.Finally,the cooperative location algorithms are studied.The Extended Kalman Filtering(EKF),Unscented Kalman Filtering(UKF)and Particle Filtering(PF)are used to fuse the pseudo-range,ranging information and location information respectively.Due to the mutual influences among the cooperative nodes in cooperative positioning,the EKF,UKF and PF algorithms are improved by resetting the error covariance matrix of the cooperative nodes at each update time.Experimental results show that after being improved,the influence between the cooperative nodes becomes smaller,and the positioning performance of the nodes is better than before.
文摘Cooperative learning emerging as the leading new approach to classroom instruction abroad over the past decades has been studied by many researchers from all aspects.This paper mainly focuses on the basics of cooperative learning and tries to answer the question that if the use of cooperative learning produce higher achievement than the traditional methods in college English reading class through experimental study.The analysis contributes to better college English teaching and learning.A conclusion is drawn that cooperative learning is very effective in improving college students reading ability.
文摘This paper provides theoretical foundation tor the problem ot localization in multi-robot formations. Sufficient and necessary conditions for completely localizing a formation of mobile robots/vehicles in SE(2) based on distributed sensor networks and graph rigidity are proposed. A method for estimating the quality of localizations via a linearized weighted least-squares algorithm is presented, which considers incomplete and noisy sensory information. The approach in this paper had been implemented in a multi-robot system of five car-like robots equipped with omni-directional cameras and IEEE 802.11b wireless network.
基金This work was supported by the National High Technology Development Program of China under Grant(No.2004AA111110,No.2006AA01A109)
文摘At present, there are many effective ways to achieve high performance in cluster system storage management, including server-end disk, server-end caching, local caching and cooperative caching. The cooperative caching mechanism shares caches among different clients so as to avoid expensive disk access costs and to improve overall throughput of cluster system. In this paper, a Single Copy Cooperative Cache model is proposed together with block lookup algorithm, block replacement algorithm and the consistency algorithm based on the model. Meanwhile, the prototype system of the model is implemented in PVFS file system. Finally, the performance of this system is tested in InfiniBand Framework, the result of which shows that in contrast to the original PVFS system, read performance of PVFS file system is improved by about two times, while write performance is reduced by nearly ten percent.