Multisensor data fusion (MDF) is an emerging technology to fuse data from multiple sensors in order to make a more accurate estimation of the environment through measurement and detection. Applications of MDF cross ...Multisensor data fusion (MDF) is an emerging technology to fuse data from multiple sensors in order to make a more accurate estimation of the environment through measurement and detection. Applications of MDF cross a wide spectrum in military and civilian areas. With the rapid evolution of computers and the proliferation of micro-mechanical/electrical systems sensors, the utilization of MDF is being popularized in research and applications. This paper focuses on application of MDF for high quality data analysis and processing in measurement and instrumentation. A practical, general data fusion scheme was established on the basis of feature extraction and merge of data from multiple sensors. This scheme integrates artificial neural networks for high performance pattern recognition. A number of successful applications in areas of NDI (Non-Destructive Inspection) corrosion detection, food quality and safety characterization, and precision agriculture are described and discussed in order to motivate new applications in these or other areas. This paper gives an overall picture of using the MDF method to increase the accuracy of data analysis and processing in measurement and instrumentation in different areas of applications.展开更多
Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc. Various multisensor data fusion methods have been extensively investigat...Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc. Various multisensor data fusion methods have been extensively investigated by researchers, of which Klaman filtering is one of the most important. Kalman filtering is the best-known recursive least mean-square algorithm to optimally estimate the unknown states of a dynamic system, which has found widespread application in many areas. The scope of the work is restricted to investigate the various data fusion and track fusion techniques based on the Kalman Filter methods, then a new method of state fusion is proposed. Finally the simulation results demonstrate the effectiveness of the introduced method.展开更多
Fin stabilizers with fin-lift feedback control can shield the mapping error of calculation between the fin angle and fin lift force,which is in the fin stabilizer with fin-angle feedback control.In practice,there are ...Fin stabilizers with fin-lift feedback control can shield the mapping error of calculation between the fin angle and fin lift force,which is in the fin stabilizer with fin-angle feedback control.In practice,there are some technical difficulties in lift fin stabilizers,such as lift force detection and lift force sensor installation,so it cannot achieve the good antirolling performance.Therefore,a fin stabilizer system with fin-lift/fin-angle integrated control is brought forward.Data fusion based on wavelet denoising technology is employed in the system,which combines lift with fin angle local information from two sensors with different frequency ranges in order to eliminate redundant and contradictory information,and using complementary information to obtain the relative integrity of the lift force signal.The system model is established in this paper,and the fusion signal and the antirolling performance of this model are simulated respectively.The result shows that the control system can meet the antirolling need in different sea situations.展开更多
The multisensor online measure system for high precision marking and cutting robot system is designed and the data fusion method is introduced, which combines augment state multiscale process with extend Kalman filter...The multisensor online measure system for high precision marking and cutting robot system is designed and the data fusion method is introduced, which combines augment state multiscale process with extend Kalman filter. The technology measuring the three-dimensional deforming information of profiled bars is applied. The experimental result shows that applying the multisensor data fusion technology can enhance the measure precision and the reliability of measure system.展开更多
The paper analyses the improvement of track loss in clutter with multisensor data fusion.By a determination of the transition probability density function for the fusion prediction error, one can study the mechanism o...The paper analyses the improvement of track loss in clutter with multisensor data fusion.By a determination of the transition probability density function for the fusion prediction error, one can study the mechanism of track loss analytically. With nearest-neighbor association algorithm. The paper we studies the fused tracking performance parameters, such as mean time to lose fused track and the cumulative probability of lost fused track versus the normalized clutter density, for track continuation and track initiation, respectively. A comparison of the results obtained with the case of a single sensor is presented. These results show that the fused tracks of multisensor reduce the possibility of track loss and improve the tracking performance. The analysis is of great importance for further understanding the action of data fusion.展开更多
In order to improve the accuracy of fusion algorithm, feedback is introduced into Kalman filtering fusion. Fusion center broadcasts its latest estimated states to the local sensors, which can improve the performance o...In order to improve the accuracy of fusion algorithm, feedback is introduced into Kalman filtering fusion. Fusion center broadcasts its latest estimated states to the local sensors, which can improve the performance of local tracking error through reducing the oovariance of each local error, and only needs calculating the trace of error variance matrices without calculating the inverse of error variance matrices. Simulation results show that it can reduce the ecmputational complexity and the oovariance of error, and it is oonvenient for engineering applications.展开更多
In distributed multisensor data fusion systems, there are two types of track fusion approaches. One is sensor track fusion with feedback information, the other is without feedback information. This paper proves that t...In distributed multisensor data fusion systems, there are two types of track fusion approaches. One is sensor track fusion with feedback information, the other is without feedback information. This paper proves that the solutions of sensor track fusion with and without feedback information are both optimal and equal.展开更多
A new multi-sensor data fusion algorithm based on EMD-MMSE was proposed.Empirical mode decomposition(EMD)is used to extract the noise of every time series for estimating the variance of the noise.Then minimum mean squ...A new multi-sensor data fusion algorithm based on EMD-MMSE was proposed.Empirical mode decomposition(EMD)is used to extract the noise of every time series for estimating the variance of the noise.Then minimum mean square error(MMSE)estimator is used to calculate the weights of the corresponding series.Finally,the fused signal is the weighted addition of all these series.The experiments in lab testified the efficiency of this method.In addition,the comparison in fusion time and fusion results with existing fusion method based on wavelet and average technique shows the advantage of this method greatly.展开更多
A data fusion method of online multisensors is prop os ed in this paper based on artificial neuron. First, the dynamic data fusion mode l on artificial neuron is built. Then the calibration of data fusion is discusse ...A data fusion method of online multisensors is prop os ed in this paper based on artificial neuron. First, the dynamic data fusion mode l on artificial neuron is built. Then the calibration of data fusion is discusse d with self-adaptive weighing technique. Finally performance of the method is d emonstrated by an online vibration measurement case. The results show that the f used data are more stable, sensitive, accurate, reliable than that of single sen sor data.展开更多
Relative navigation is crucial for spacecraft noncooperative rendezvous,and angles-only navigation using visible and infrared cameras provides a feasible solution.Herein,an angles-only navigation algorithm with multis...Relative navigation is crucial for spacecraft noncooperative rendezvous,and angles-only navigation using visible and infrared cameras provides a feasible solution.Herein,an angles-only navigation algorithm with multisensor data fusion is proposed to derive the relative motion states between two noncooperative spacecraft.First,the design model of the proposed algorithm is introduced,including the derivation of the state propagation and measurement equations.Subsequently,models for the sensor and actuator are introduced,and the effects of various factors on the sensors and actuators are considered.The square-root unscented Kalman filter is used to design the angles-only navigation filtering scherne.Additionally,the Clohessy-Wiltshire terminal guidance algorithm is introducedto obtain the theoretical relative motion trajectories during the rendezvous operations of two noncooperative spacecraft.Finally,the effectiveness of the proposed angles-only navigation algorithm is verified using a semi-physical simulation platform.The results prove that an optical navigation camera combined with average accelerometers and occasional orbital maneuvers is feasible for spacecraft noncooperative rendezvous using angles-only navigation.展开更多
The optimal fusion solution with feedback information for a hybrid multisensor data fusion system is presented. In this system, a part of sensors process their data locally to produce local tracks, and another part of...The optimal fusion solution with feedback information for a hybrid multisensor data fusion system is presented. In this system, a part of sensors process their data locally to produce local tracks, and another part of sensors only provide detection reports These tracks and detection reports are communicated to a central site where track fusion and composite filtering are performed. The comparative results on the simulations suggest the feedback information from the center can greatly improve the tracking performance of the local node.展开更多
Purpose–Data integration is to combine data residing at different sources and to provide the users with a unified interface of these data.An important issue on data integration is the existence of conflicts among the...Purpose–Data integration is to combine data residing at different sources and to provide the users with a unified interface of these data.An important issue on data integration is the existence of conflicts among the different data sources.Data sources may conflict with each other at data level,which is defined as data inconsistency.The purpose of this paper is to aim at this problem and propose a solution for data inconsistency in data integration.Design/methodology/approach–A relational data model extended with data source quality criteria is first defined.Then based on the proposed data model,a data inconsistency solution strategy is provided.To accomplish the strategy,fuzzy multi-attribute decision-making(MADM)approach based on data source quality criteria is applied to obtain the results.Finally,users feedbacks strategies are proposed to optimize the result of fuzzy MADM approach as the final data inconsistent solution.Findings–To evaluate the proposed method,the data obtained from the sensors are extracted.Some experiments are designed and performed to explain the effectiveness of the proposed strategy.The results substantiate that the solution has a better performance than the other methods on correctness,time cost and stability indicators.Practical implications–Since the inconsistent data collected from the sensors are pervasive,the proposed method can solve this problem and correct the wrong choice to some extent.Originality/value–In this paper,for the first time the authors study the effect of users feedbacks on integration results aiming at the inconsistent data.展开更多
针对实物保护系统(Physical Protection System,PPSY)中单一传感器报警准确率较低的问题,提出了一种基于改进ID3的CAC-ID3(Confidence And Correlation-ID3)算法在多传感器实物保护系统中数据融合的新方法。与传统的单一传感器数据信息...针对实物保护系统(Physical Protection System,PPSY)中单一传感器报警准确率较低的问题,提出了一种基于改进ID3的CAC-ID3(Confidence And Correlation-ID3)算法在多传感器实物保护系统中数据融合的新方法。与传统的单一传感器数据信息处理相比,多传感器数据融合能够更加准确、全面的得到被测对象的数据信息,有效地利用多传感器资源。CAC-ID3算法首先在ID3的基础上引入属性置信度重新计算期望熵,解决属性和价值不对等的问题,克服多传感器数据分类时多值偏向的缺点,其值由经验和相关领域知识决定。然后通过引入属性间的相关度来调整信息增益值,提高分类精度。实验结果表明:基于CAC-ID3的决策树算法的多传感器PPSY能有效提高报警准确率和可靠性,防止敌对分子入侵,提高传感器对PPSY的检测的效能,且该算法的分类精度高于ID3算法。展开更多
A new 3 D fusion tracking system for an anti air missile homing system based on radar and imaging sensor is developed. The attitude measurements from the imaging sensor are used to improve the tracking performance. ...A new 3 D fusion tracking system for an anti air missile homing system based on radar and imaging sensor is developed. The attitude measurements from the imaging sensor are used to improve the tracking performance. Computer simulation results show that the tracking system greatly reduces the tracking errors compared with trackers without attitude measurements, and achieves small miss distances even when the target has a big maneuver.展开更多
The multisensor detection area partitioning is considered. An approach is presented to the fusion in each detection area where the sensor uses different thresholds and then at system level. The expressions of the dete...The multisensor detection area partitioning is considered. An approach is presented to the fusion in each detection area where the sensor uses different thresholds and then at system level. The expressions of the detection probability and false alarm probability are given. An application of the method is illustrated to distributed CFAR detection systems. The result shows that the system detection probability may be improved by setting different thresholds for a detector.展开更多
A decentralized parallel one-pass deconvolution algorithm for multisensor systems with multiplicative noises is proposed. Comparing with the conventional deconvolution algorithm, it avoids the computational overload a...A decentralized parallel one-pass deconvolution algorithm for multisensor systems with multiplicative noises is proposed. Comparing with the conventional deconvolution algorithm, it avoids the computational overload and the high storage requirement. The algorithm is optimal in the sense of linear minimum-variance. The simulation results illustrate the validity of the proposed algorithm.展开更多
文摘Multisensor data fusion (MDF) is an emerging technology to fuse data from multiple sensors in order to make a more accurate estimation of the environment through measurement and detection. Applications of MDF cross a wide spectrum in military and civilian areas. With the rapid evolution of computers and the proliferation of micro-mechanical/electrical systems sensors, the utilization of MDF is being popularized in research and applications. This paper focuses on application of MDF for high quality data analysis and processing in measurement and instrumentation. A practical, general data fusion scheme was established on the basis of feature extraction and merge of data from multiple sensors. This scheme integrates artificial neural networks for high performance pattern recognition. A number of successful applications in areas of NDI (Non-Destructive Inspection) corrosion detection, food quality and safety characterization, and precision agriculture are described and discussed in order to motivate new applications in these or other areas. This paper gives an overall picture of using the MDF method to increase the accuracy of data analysis and processing in measurement and instrumentation in different areas of applications.
文摘Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc. Various multisensor data fusion methods have been extensively investigated by researchers, of which Klaman filtering is one of the most important. Kalman filtering is the best-known recursive least mean-square algorithm to optimally estimate the unknown states of a dynamic system, which has found widespread application in many areas. The scope of the work is restricted to investigate the various data fusion and track fusion techniques based on the Kalman Filter methods, then a new method of state fusion is proposed. Finally the simulation results demonstrate the effectiveness of the introduced method.
基金supported by the "Ship Control Engineering" Emphasis Project of 211 Engineering in the Tenth Five-Year Plan
文摘Fin stabilizers with fin-lift feedback control can shield the mapping error of calculation between the fin angle and fin lift force,which is in the fin stabilizer with fin-angle feedback control.In practice,there are some technical difficulties in lift fin stabilizers,such as lift force detection and lift force sensor installation,so it cannot achieve the good antirolling performance.Therefore,a fin stabilizer system with fin-lift/fin-angle integrated control is brought forward.Data fusion based on wavelet denoising technology is employed in the system,which combines lift with fin angle local information from two sensors with different frequency ranges in order to eliminate redundant and contradictory information,and using complementary information to obtain the relative integrity of the lift force signal.The system model is established in this paper,and the fusion signal and the antirolling performance of this model are simulated respectively.The result shows that the control system can meet the antirolling need in different sea situations.
文摘The multisensor online measure system for high precision marking and cutting robot system is designed and the data fusion method is introduced, which combines augment state multiscale process with extend Kalman filter. The technology measuring the three-dimensional deforming information of profiled bars is applied. The experimental result shows that applying the multisensor data fusion technology can enhance the measure precision and the reliability of measure system.
文摘The paper analyses the improvement of track loss in clutter with multisensor data fusion.By a determination of the transition probability density function for the fusion prediction error, one can study the mechanism of track loss analytically. With nearest-neighbor association algorithm. The paper we studies the fused tracking performance parameters, such as mean time to lose fused track and the cumulative probability of lost fused track versus the normalized clutter density, for track continuation and track initiation, respectively. A comparison of the results obtained with the case of a single sensor is presented. These results show that the fused tracks of multisensor reduce the possibility of track loss and improve the tracking performance. The analysis is of great importance for further understanding the action of data fusion.
文摘In order to improve the accuracy of fusion algorithm, feedback is introduced into Kalman filtering fusion. Fusion center broadcasts its latest estimated states to the local sensors, which can improve the performance of local tracking error through reducing the oovariance of each local error, and only needs calculating the trace of error variance matrices without calculating the inverse of error variance matrices. Simulation results show that it can reduce the ecmputational complexity and the oovariance of error, and it is oonvenient for engineering applications.
文摘In distributed multisensor data fusion systems, there are two types of track fusion approaches. One is sensor track fusion with feedback information, the other is without feedback information. This paper proves that the solutions of sensor track fusion with and without feedback information are both optimal and equal.
基金The National High Technology Research and Development Program of China(863Program)(No.2001AA602021)
文摘A new multi-sensor data fusion algorithm based on EMD-MMSE was proposed.Empirical mode decomposition(EMD)is used to extract the noise of every time series for estimating the variance of the noise.Then minimum mean square error(MMSE)estimator is used to calculate the weights of the corresponding series.Finally,the fused signal is the weighted addition of all these series.The experiments in lab testified the efficiency of this method.In addition,the comparison in fusion time and fusion results with existing fusion method based on wavelet and average technique shows the advantage of this method greatly.
文摘A data fusion method of online multisensors is prop os ed in this paper based on artificial neuron. First, the dynamic data fusion mode l on artificial neuron is built. Then the calibration of data fusion is discusse d with self-adaptive weighing technique. Finally performance of the method is d emonstrated by an online vibration measurement case. The results show that the f used data are more stable, sensitive, accurate, reliable than that of single sen sor data.
基金supported by the China Aerospace Science and Technology Corporation Eighth Research Institute Industry-University-Research Cooperation Fund(SAST 2020-019).
文摘Relative navigation is crucial for spacecraft noncooperative rendezvous,and angles-only navigation using visible and infrared cameras provides a feasible solution.Herein,an angles-only navigation algorithm with multisensor data fusion is proposed to derive the relative motion states between two noncooperative spacecraft.First,the design model of the proposed algorithm is introduced,including the derivation of the state propagation and measurement equations.Subsequently,models for the sensor and actuator are introduced,and the effects of various factors on the sensors and actuators are considered.The square-root unscented Kalman filter is used to design the angles-only navigation filtering scherne.Additionally,the Clohessy-Wiltshire terminal guidance algorithm is introducedto obtain the theoretical relative motion trajectories during the rendezvous operations of two noncooperative spacecraft.Finally,the effectiveness of the proposed angles-only navigation algorithm is verified using a semi-physical simulation platform.The results prove that an optical navigation camera combined with average accelerometers and occasional orbital maneuvers is feasible for spacecraft noncooperative rendezvous using angles-only navigation.
文摘The optimal fusion solution with feedback information for a hybrid multisensor data fusion system is presented. In this system, a part of sensors process their data locally to produce local tracks, and another part of sensors only provide detection reports These tracks and detection reports are communicated to a central site where track fusion and composite filtering are performed. The comparative results on the simulations suggest the feedback information from the center can greatly improve the tracking performance of the local node.
文摘Purpose–Data integration is to combine data residing at different sources and to provide the users with a unified interface of these data.An important issue on data integration is the existence of conflicts among the different data sources.Data sources may conflict with each other at data level,which is defined as data inconsistency.The purpose of this paper is to aim at this problem and propose a solution for data inconsistency in data integration.Design/methodology/approach–A relational data model extended with data source quality criteria is first defined.Then based on the proposed data model,a data inconsistency solution strategy is provided.To accomplish the strategy,fuzzy multi-attribute decision-making(MADM)approach based on data source quality criteria is applied to obtain the results.Finally,users feedbacks strategies are proposed to optimize the result of fuzzy MADM approach as the final data inconsistent solution.Findings–To evaluate the proposed method,the data obtained from the sensors are extracted.Some experiments are designed and performed to explain the effectiveness of the proposed strategy.The results substantiate that the solution has a better performance than the other methods on correctness,time cost and stability indicators.Practical implications–Since the inconsistent data collected from the sensors are pervasive,the proposed method can solve this problem and correct the wrong choice to some extent.Originality/value–In this paper,for the first time the authors study the effect of users feedbacks on integration results aiming at the inconsistent data.
文摘针对实物保护系统(Physical Protection System,PPSY)中单一传感器报警准确率较低的问题,提出了一种基于改进ID3的CAC-ID3(Confidence And Correlation-ID3)算法在多传感器实物保护系统中数据融合的新方法。与传统的单一传感器数据信息处理相比,多传感器数据融合能够更加准确、全面的得到被测对象的数据信息,有效地利用多传感器资源。CAC-ID3算法首先在ID3的基础上引入属性置信度重新计算期望熵,解决属性和价值不对等的问题,克服多传感器数据分类时多值偏向的缺点,其值由经验和相关领域知识决定。然后通过引入属性间的相关度来调整信息增益值,提高分类精度。实验结果表明:基于CAC-ID3的决策树算法的多传感器PPSY能有效提高报警准确率和可靠性,防止敌对分子入侵,提高传感器对PPSY的检测的效能,且该算法的分类精度高于ID3算法。
文摘A new 3 D fusion tracking system for an anti air missile homing system based on radar and imaging sensor is developed. The attitude measurements from the imaging sensor are used to improve the tracking performance. Computer simulation results show that the tracking system greatly reduces the tracking errors compared with trackers without attitude measurements, and achieves small miss distances even when the target has a big maneuver.
基金Supported by the Defense Pre-research Foundation
文摘The multisensor detection area partitioning is considered. An approach is presented to the fusion in each detection area where the sensor uses different thresholds and then at system level. The expressions of the detection probability and false alarm probability are given. An application of the method is illustrated to distributed CFAR detection systems. The result shows that the system detection probability may be improved by setting different thresholds for a detector.
基金Supported in part by the University of Colorado, the US National Science Foundation (Grants CMS-9625086,CMS-0201459, IIS-9711936, and HRD-0095944) the US Office of Naval Research (Grants N00014-97-1-0642 and N00014-02-1-0136) the Colorado Center for Information Storage, the Colorado Advanced Software Institute, Maxtor Corporation, Quantum Corporation, Storage Technology Corporation, and Data Fusion Corporation
文摘Research in control systems, sensor fusion and haptic interfaces is reviewed.
基金This work was supported by the Science&Technology Research Key Projects of Ministry of Education of China.
文摘A decentralized parallel one-pass deconvolution algorithm for multisensor systems with multiplicative noises is proposed. Comparing with the conventional deconvolution algorithm, it avoids the computational overload and the high storage requirement. The algorithm is optimal in the sense of linear minimum-variance. The simulation results illustrate the validity of the proposed algorithm.