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An Improved Blockchain-Empowered Storage Service Based on Data Association 认领 引用
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作者 Bin Fang Qi Yu +2 位作者 Han Wu Xingxing Hou Jingyu Zhang 《Computers, Materials & Continua》 SCIE EI 2026年第8期1650-1672,共23页
The integration of Internet of Things(IoT)with blockchain technology introduces significant challenges in handling massive and frequent transaction data generated by distributed IoT devices.The Unspent Transaction Out... The integration of Internet of Things(IoT)with blockchain technology introduces significant challenges in handling massive and frequent transaction data generated by distributed IoT devices.The Unspent Transaction Output(UTXO)model,widely adopted in blockchain systems like Bitcoin,faces critical scalability issues when applied to IoT environments.This is because the datasets it processes expand rapidly,which consumes a large amount of memory and increases the disk access latency of resource-constrained IoT nodes.Existing optimization approaches exhibit limitations in dynamic adaptability and protocol compatibility.To address these challenges,we propose an improved blockchain-empowered storage service that introduces a data association-based multi-zone storage framework for UTXO-based blockchain systems.This service establishes a predictive model for UTXO access probability by analyzing IoT device transaction time intervals and address-specific frequencies.Subsequently,we design a dynamic three-zone storage framework that intelligently optimizes UTXO placement.Experimental results demonstrate that our approach significantly reduces disk access and optimizes memory usage compared with prevalent algorithms,while maintaining compatibility with existing UTXO-based protocols. 展开更多
关键词 Blockchain systems data association storage optimization memory utilization storage services
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Learning Manipulation from Expert Demonstrations Based on Multiple Data Associations and Physical Constraints 认领 引用
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作者 Yangqing Ye Yaojie Mao +5 位作者 Shiming Qiu Chuan’guo Tang Zhirui Pan Weiwei Wan Shibo Cai Guanjun Bao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2025年第2期279-294,共16页
Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in ... Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in a more versatile and effective manner:acquiring skills through mere“observation”.Video to Command task is widely perceived as a promising approach for task-based learning,which yet faces two key challenges:(1)High redundancy and low frame rate of fine-grained action sequences make it difficult to manipulate objects robustly and accurately.(2)Video to Command models often prioritize accuracy and richness of output commands over physical capabilities,leading to impractical or unsafe instructions for robots.This article presents a novel Video to Command framework that employs multiple data associations and physical constraints.First,we introduce an object-level appearancecontrasting multiple data association strategy to effectively associate manipulated objects in visually complex environments,capturing dynamic changes in video content.Then,we propose a multi-task Video to Command model that utilizes object-level video content changes to compile expert demonstrations into manipulation commands.Finally,a multi-task hybrid loss function is proposed to train a Video to Command model that adheres to the constraints of the physical world and manipulation tasks.Our method achieved over 10%on BLEU_N,METEOR,ROUGE_L,and CIDEr compared to the up-to-date methods.The dual-arm robot prototype was established to demonstrate the whole process of learning from an expert demonstration of multiple skills and then executing the tasks by a robot. 展开更多
关键词 Videos to command Multiple data associations Multi-task model Multi-task hybrid loss function Physical constraints
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Modified joint probabilistic data association with classification-aided for multitarget tracking 认领 引用 被引量：9
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作者 Ba Hongxin Cao Lei +1 位作者 He Xinyi Cheng Qun 《Journal of Systems Engineering and Electronics》 SCIE EI 2008年第3期434-439,共6页
Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are... Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are similar for different closely spaced targets, there is ambiguity in using the kinematic information alone; the correct association probability will decrease in conventional joint probabilistic data association algorithm and track coalescence will occur easily. A modified algorithm of joint probabilistic data association with classification-aided is presented, which avoids track coalescence when tracking multiple neighboring targets. Firstly, an identification matrix is defined, which is used to simplify validation matrix to decrease computational complexity. Then, target class information is integrated into the data association process. Performance comparisons with and without the use of class information in JPDA are presented on multiple closely spaced maneuvering targets tracking problem. Simulation results quantify the benefits of classification-aided JPDA for improved multiple targets tracking, especially in the presence of association uncertainty in the kinematic measurement and target maneuvering. Simulation results indicate that the algorithm is valid. 展开更多
关键词 multi-target tracking data association joint probabilistic data association classification information,track coalescence maneuvering target.
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FGAs-Based Data Association Algorithm for Multi-sensor Multi-target Tracking 认领 引用 被引量：7
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作者 朱力立 张焕春 经亚枝 《Chinese Journal of Aeronautics》 EI CAS 2003年第3期177-181,共5页
A novel data association algorithm is developed based on fuzzy geneticalgorithms (FGAs). The static part of data association uses one FGA to determine both the lists ofcomposite measurements and the solutions of m-bes... A novel data association algorithm is developed based on fuzzy geneticalgorithms (FGAs). The static part of data association uses one FGA to determine both the lists ofcomposite measurements and the solutions of m-best S-D assignment. In the dynamic part of dataassociation, the results of the m-best S-D assignment are then used in turn, with a Kalman filterstate estimator, in a multi-population FGA-based dynamic 2D assignment algorithm to estimate thestates of the moving targets over time. Such an assignment-based data association algorithm isdemonstrated on a simulated passive sensor track formation and maintenance problem. The simulationresults show its feasibility in multi-sensor multi-target tracking. Moreover, algorithm developmentand real-time problems are briefly discussed. 展开更多
关键词 multi-target tracking data association FGA assignment problem kalmanfilter
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Loopy belief propagation based data association for extended target tracking 认领 引用 被引量：4
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作者 Zhenzhen SU Hongbing JI Yongquan ZHANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2020年第8期2212-2223,共12页
The data association problem of multiple extended target tracking is very challenging because each target may generate multiple measurements.Recently,the belief propagation based multiple target tracking algorithms wi... The data association problem of multiple extended target tracking is very challenging because each target may generate multiple measurements.Recently,the belief propagation based multiple target tracking algorithms with high efficiency have been a research focus.Different from the belief propagation based Extended Target tracking based on Belief Propagation(ET-BP)algorithm proposed in our previous work,a new graphical model formulation of data association for multiple extended target tracking is proposed in this paper.The proposed formulation can be solved by the Loopy Belief Propagation(LBP)algorithm.Furthermore,the simplified measurement set in the ET-BP algorithm is modified to improve tracking accuracy.Finally,experiment results show that the proposed algorithm has better performance than the ET-BP and joint probabilistic data association based on the simplified measurement set algorithms in terms of accuracy and efficiency.Additionally,the convergence of the proposed algorithm is verified in the simulations. 展开更多
关键词 Belief propagation Data association Extended target Graphical model Simplified measurement set Target tracking
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Study on the Hungarian algorithm for the maximum likelihood data association problem 认领 引用 被引量：6
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作者 Wang Jianguo He Peikun Cao Wei 《Journal of Systems Engineering and Electronics》 SCIE EI 2007年第1期27-32,共6页
A specialized Hungarian algorithm was developed here for the maximum likelihood data association problem with two implementation versions due to presence of false alarms and missed detections. The maximum likelihood d... A specialized Hungarian algorithm was developed here for the maximum likelihood data association problem with two implementation versions due to presence of false alarms and missed detections. The maximum likelihood data association problem is formulated as a bipartite weighted matching problem. Its duality and the optimality conditions are given. The Hungarian algorithm with its computational steps, data structure and computational complexity is presented. The two implementation versions, Hungarian forest （HF） algorithm and Hungarian tree （HT） algorithm, and their combination with the naYve auction initialization are discussed. The computational results show that HT algorithm is slightly faster than HF algorithm and they are both superior to the classic Munkres algorithm. 展开更多
关键词 Tracking Data association Linear programming Hungarian algorithm
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Data association based on target signal classification information 认领 引用 被引量：3
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作者 Guo Lei Tang Bin Liu Gang 《Journal of Systems Engineering and Electronics》 SCIE EI 2008年第2期246-251,共6页
In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too... In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too close to each other. To enhance the tracking accuracy, the target signal classification information （TSCI） should be used to improve the data association. The TSCI is integrated in the data association process using the JPDA （joint probabilistic data association）. The use of the TSCI in the data association can improve discrimination by yielding a purer track and preserving continuity. To verify the validity of the application of TSCI, two simulation experiments are done on an air target-tracing problem, that is, one using the TSCI and the other not using the TSCI. The final comparison shows that the use of the TSCI can effectively improve tracking accuracy. 展开更多
关键词 passive tracking joint probabilistic data association target signal classification information.
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Study on data association algorithm of multi-passive-sensor location system 认领 引用 被引量：3
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作者 周莉 何友 张维华 《Journal of Systems Engineering and Electronics》 2005年第3期489-493,共5页
Aiming at three-passive-sensor location system, a generalized 3-dimension （3-D） assignment model is constructed based on property information, and a multi-target programming model is proposed based on direction-find... Aiming at three-passive-sensor location system, a generalized 3-dimension （3-D） assignment model is constructed based on property information, and a multi-target programming model is proposed based on direction-finding and property fusion information. The multi-target programming model is transformed into a single target programming problem to resolve, and its data association result is compared with the results which are solved by using one kind of information only. Simulation experiments show the effectiveness of the multi-target programming algorithm with higher data association accuracy and less calculation. 展开更多
关键词 data association algorithm multi-target programming model joint information cost matrix.
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Scene-adaptive hierarchical data association and depth-invariant part-based appearance model for indoor multiple objects tracking 认领 引用 被引量：1
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作者 Hong Liu Can Wang Yuan Gao 《CAAI Transactions on Intelligence Technology》 2016年第3期210-224,共15页
Indoor multi-tracking is more challenging compared with outdoor tasks due to frequent occlusion, view-truncation, severe scale change and pose variation, which may bring considerable unreliability and ambiguity to tar... Indoor multi-tracking is more challenging compared with outdoor tasks due to frequent occlusion, view-truncation, severe scale change and pose variation, which may bring considerable unreliability and ambiguity to target representation and data association. So discriminative and reliable target representation is vital for accurate data association in multi-tracking. Pervious works always combine bunch of features to increase the discriminative power, but this is prone to error accumulation and unnecessary computational cost, which may increase ambiguity on the contrary. Moreover, reliability of a same feature in different scenes may vary a lot, especially for currently widespread network cameras, which are settled in various and complex indoor scenes, previous fixed feature selection schemes cannot meet general requirements. To properly handle these problems, first, we propose a scene-adaptive hierarchical data association scheme, which adaptively selects features with higher reliability on target representation in the applied scene, and gradually combines features to the minimum requirement of discriminating ambiguous targets; second, a novel depth-invariant part-based appearance model using RGB-D data is proposed which makes the appearance model robust to scale change, partial occlusion and view-truncation. The introduce of RGB-D data increases the diversity of features, which provides more types of features for feature selection in data association and enhances the final multi-tracking performance. We validate our method from several aspects including scene-adaptive feature selection scheme, hierarchical data association scheme and RGB-D based appearance modeling scheme in various indoor scenes, which demonstrates its effectiveness and efficiency on improving multi-tracking performances in various indoor scenes. 展开更多
关键词 Multiple objects tracking Scene-adaptive Data association Appearance model RGB-D data
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New data association technique based on ACO with directional information considered 认领 引用
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作者 Kang Li Xie Weixin Huang Jingxiong 《Journal of Systems Engineering and Electronics》 SCIE EI 2008年第6期1283-1286,共4页
Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the conc... Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the concept for tour and the length of tour are redefined. Additionally, the directional information is incorporated into the proposed method because it is one of the most important factors that affects the performance of data association. Kalman filter is employed to estimate target states. Computer simulation results show that the proposed method could carry out data association in an acceptable CPU time, and the correct data association rate is higher than that obtained by the data association （DA） algorithm not combined with directional information. 展开更多
关键词 ant colony optimization data association target tracking directional information
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Probabilistic data association algorithm based on ensemble Kalman filter with observation iterated update 认领 引用
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作者 胡振涛 Fu Chunling Li Junwei 《High Technology Letters》 EI CAS 2015年第3期301-308,共8页
Aiming at improving the observation uncertainty caused by limited accuracy of sensors,and the uncertainty of observation source in clutters,through the dynamic combination of ensemble Kalman filter(EnKF) and probabili... Aiming at improving the observation uncertainty caused by limited accuracy of sensors,and the uncertainty of observation source in clutters,through the dynamic combination of ensemble Kalman filter(EnKF) and probabilistic data association(PDA),a novel probabilistic data association algorithm based on ensemble Kalman filter with observation iterated update is proposed.Firstly,combining with the advantages of data assimilation handling observation uncertainty in EnKF,an observation iterated update strategy is used to realize optimization of EnKF in structure.And the object is to further improve state estimation precision of nonlinear system.Secondly,the above algorithm is introduced to the framework of PDA,and the object is to increase reliability and stability of candidate echo acknowledgement.In addition,in order to decrease computation complexity in the combination of improved EnKF and PDA,the maximum observation iterated update mechanism is applied to the iteration of PDA.Finally,simulation results verify the feasibility and effectiveness of the proposed algorithm by a typical target tracking scene in clutters. 展开更多
关键词 nonlinear filter observation iterated update ensemble Kalman filter （EnKF） probabilistic data association （PDA）
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SEQUENTIAL ALGORITHM FOR MULTISENSOR PROBABILISTIC DATA ASSOCIATION 认领 引用
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作者 Hu Wenlong Mao Shiyi 《Chinese Journal of Aeronautics》 CAS 1997年第2期144-150,共7页
Based upon a multisensor sequential processing filter, the target states in a3D Cartesian system are projected into the measurement space of each sensor to extend thejoint probabilistic data association (JPDA) algorit... Based upon a multisensor sequential processing filter, the target states in a3D Cartesian system are projected into the measurement space of each sensor to extend thejoint probabilistic data association (JPDA) algorithm into the multisensor tracking systemsconsisting of heterogeneous sensors for the data association. 展开更多
关键词 multiple target tracking sensors sequential analysis data association data fusion
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A combination algorithm of Chaos optimization and genetic algorithm and its application in maneuvering multiple targets data association 认领 引用
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作者 王建华 张琳 刘维亭 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2007年第4期470-473,共4页
The most important problem in targets tracking is data association which may be represented as a sort of constraint combinational optimization problem. Chaos optimization and adaptive genetic algorithm were used to de... The most important problem in targets tracking is data association which may be represented as a sort of constraint combinational optimization problem. Chaos optimization and adaptive genetic algorithm were used to deal with the problem of multi-targets data association separately. Based on the analysis of the limitation of chaos optimization and genetic algorithm, a new chaos genetic optimization combination algorithm was presented. This new algorithm first applied the "rough" search of chaos optimization to initialize the population of GA, then optimized the population by real-coded adaptive GA. In this way, GA can not only jump out of the "trap" of local optimal results easily but also increase the rate of convergence. And the new method can also avoid the complexity and time-consumed limitation of conventional way. The simulation results show that the combination algorithm can obtain higher correct association percent and the effect of association is obviously superior to chaos optimization or genetic algorithm separately. This method has better convergence property as well as time property than the conventional ones. 展开更多
关键词 data association chaos optimization genetic algorithm maneuvering multiple targets tracking
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Novel Grouped Probability Data Association Algorithm for MIMO Detection 认领 引用
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作者 车文 赵慧 王文博 《Journal of Beijing Institute of Technology》 EI CAS 2008年第1期67-70,共4页
To bridge the performance gap between original probability data association （PDA） algorithm and the optimum maximum a posterior （MAP） algorithm for multi-input multi-output （MIMO） detection, a grouped PDA （GP-... To bridge the performance gap between original probability data association （PDA） algorithm and the optimum maximum a posterior （MAP） algorithm for multi-input multi-output （MIMO） detection, a grouped PDA （GP-PDA） detection algorithm is proposed. The proposed GP-PDA method divides all the transmit antennas into groups, and then updates the symbol probabilities group by group using PDA computations. In each group, joint a posterior probability （APP） is computed to obtain the APP of a single symbol in this group, like the MAP algorithm. Such new algorithm combines the characters of MAP and PDA. MAP and original PDA algorithm can be regarded as a special case of the proposed GP-PDA. Simulations show that the proposed GP-PDA provides a performance and complexity trade, off between original PDA and MAP algorithm. 展开更多
关键词 multi-input multi-output （MIMO） V-BLAST group probability data association （PDA）
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A gate size estimation algorithm for data association filters 认领 引用 被引量：6
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作者 WANG MingHui WAN Qun YOU ZhiSheng 《Science in China(Series F)》 2008年第4期425-432,共8页
The problem of forming validation regions or gates for new sensor measurements obtained when tracking targets in clutter is considered. Since the gate size is an integral part of the data association filter, this pape... The problem of forming validation regions or gates for new sensor measurements obtained when tracking targets in clutter is considered. Since the gate size is an integral part of the data association filter, this paper is intended to describe a way of estimating the gate size via the performance of the data association filter. That is, the gate size can be estimated by looking for the optimal performance of the data association filter. Simulations show that this estimation method of the gate size offers advantages over the common and classical estimation methods of the gate size, especially in a heavy clutter and/or false alarm environment. 展开更多
关键词 data association filter gate size optimal estimation
Multi-target pig tracking algorithm based on joint probability data association and particle filter 认领 引用 被引量：2
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作者 Longqing Sun Yiyang Li 《International Journal of Agricultural and Biological Engineering》 SCIE 2021年第4期199-207,共9页
In order to evaluate the health status of pigs in time,monitor accurately the disease dynamics of live pigs,and reduce the morbidity and mortality of pigs in the existing large-scale farming model,pig detection and tr... In order to evaluate the health status of pigs in time,monitor accurately the disease dynamics of live pigs,and reduce the morbidity and mortality of pigs in the existing large-scale farming model,pig detection and tracking technology based on machine vision are used to monitor the behavior of pigs.However,it is challenging to efficiently detect and track pigs with noise caused by occlusion and interaction between targets.In view of the actual breeding conditions of pigs and the limitations of existing behavior monitoring technology of an individual pig,this study proposed a method that used color feature,target centroid and the minimum circumscribed rectangle length-width ratio as the features to build a multi-target tracking algorithm,which based on joint probability data association and particle filter.Experimental results show the proposed algorithm can quickly and accurately track pigs in the video,and it is able to cope with partial occlusions and recover the tracks after temporary loss. 展开更多
关键词 joint probability data association pig tracking particle filter centroid
New optimal algorithm of data association for multi-passive-sensor location system 认领 引用 被引量：2
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作者 ZHOU Li HE YOU ZHANG WeiHua 《Science in China(Series F)》 2007年第4期600-608,共9页
In dense target and false detection scenario of four time difference of arrival （TDOA） for multi-passive-sensor location system, the global optimal data association algorithm has to be adopted. In view of the heavy ... In dense target and false detection scenario of four time difference of arrival （TDOA） for multi-passive-sensor location system, the global optimal data association algorithm has to be adopted. In view of the heavy calculation burden of the traditional optimal assignment algorithm, this paper proposes a new global optimal assignment algorithm and a 2-stage association algorithm based on a statistic test. Compared with the traditional optimal algorithm, the new optimal algorithm avoids the complicated operations for finding the target position before we calculate association cost; hence, much of the procedure time is saved. In the 2-stage association algorithm, a large number of false location points are eliminated from candidate associations in advance. Therefore, the operation is further decreased, and the correct data association probability is improved in varying degrees. Both the complexity analyses and simulation results can verify the effectiveness of the new algorithms. 展开更多
关键词 optimal assignment algorithm data association 2-stage association algorithm multi-passive-sensor location system distance difference of arrival （DDOA）
Distributed interacted multisensor joint probabilistic data association algorithm based on D-S theory 认领 引用 被引量：2
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作者 ZHANG Jingwei XIU Jianjuan HE You XlONG Wei 《Science in China(Series F)》 2006年第2期219-227,共9页
In order to resolve the multisensor multiplied maneuvering target tracking problem, this paper presents a distributed interacted multiple model multisensor joint probabilistic data association algorithm （DIMM-MSJPDA... In order to resolve the multisensor multiplied maneuvering target tracking problem, this paper presents a distributed interacted multiple model multisensor joint probabilistic data association algorithm （DIMM-MSJPDA）. First of all, the interacted multiple model joint probabilistic data association algorithm is applied to each sensor, and then the state estimation, estimation covariance, model probability, combined innovation, innovation covariance are delivered to the fusion center. Then, the tracks from each sensor are correlated and the D-S evidence theory is used to gain the model probability of an identical target. Finally, the ultimate state estimation of each target is calculated according to the new model probability, and the state estimation is transmitted to each sensor. Simulations are designed to test the tracking performance of DIMM-MSJPDA algorithm. The results show that the use of DIMM-MSJPDA algorithm enables the distributed multisensor system to track multiplied maneuvering targets and its tracking performance is much better than that of IMMJPDA algorithm. 展开更多
关键词 distributed interacted multisensor data association.
D-DeepOCSORT: multi-object tracking algorithm based on LiDAR and monocular camera 认领 引用
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作者 Xiao HE Shuai REN +1 位作者 Chang LIU Lei SHI 《Optoelectronics Letters》 EI 2026年第2期118-123,共6页
To enhance the tracking stability of Deep OCSORT, this paper proposes a novel multi-sensor data fusion-based multi-object tracking(MOT) method. Specifically, we build upon the Deep OCSORT foundation and additionally i... To enhance the tracking stability of Deep OCSORT, this paper proposes a novel multi-sensor data fusion-based multi-object tracking(MOT) method. Specifically, we build upon the Deep OCSORT foundation and additionally integrate target velocity information directly measured by light detection and ranging(Li DAR). The introduction of this velocity information is conducted from three perspectives. Firstly, during data association, a penalty term is constructed based on the differences in target velocities to constrain generating matches with consistent velocities. Secondly, use Li DAR velocity for initialization and online updating of the velocity state within the tracker, making tracking predictions more stable. Thirdly, control the degree of dependence on velocity information by adjusting the process noise covariance matrix. Evaluation results on the KITTI dataset demonstrate that compared to the original Deep OCSORT, the proposed improved multi-source heterogeneous information fusion method significantly enhances tracking performance, with maximum improvements of 3.35, 3.26, and 3.71 on the higher order tracking accuracy(HOTA), multi-object tracking accuracy(MOTA), and interaction detection F1 score(IDF1) metrics, respectively. This study provides an effective approach to building a more stable and accurate MOT system. 展开更多
关键词 light detection ranging li dar enhance tracking stability penalty term velocity information integrate target velocity information deep ocsort foundation data association deep ocsort
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DATA FUSION ALGORITHM BASED ON STATE AND ATTRIBUTE PARAMETER 认领 引用 被引量：2
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作者 康伟 潘泉 +1 位作者 张洪才 戴冠中 《Chinese Journal of Aeronautics》 EI CAS 1999年第2期38-43,共6页
A new data fusion algorithm is presented. The new algorithm has two steps. First, three basic probability assignments dependent on different attribute parameters with Demspter fusion rule are processed. Using the fusi... A new data fusion algorithm is presented. The new algorithm has two steps. First, three basic probability assignments dependent on different attribute parameters with Demspter fusion rule are processed. Using the fusion results, one can calculate the evidence interval of the proposition that “the return is from target”. Then based on the magnitude of the center of the evidence interval, one can reject some false alarms, so as to cut down the number of clutters accepted by the filter gate. Second, the attribute parameter likelihood function(APLF, for short) and kinematic measurement likelihood function are used to form a joint likelihood function. A method is also proposed for calculating APLF. As for APLF, it is found and proved that there are differences between similar targets and dissimlar targets. By using the differences, one can distinguish adjacent targets more efficiently. In a word, the technique presented in this paper is an integrated adaptive data association fusion algorithm. The advantages of the algorithm are discussed and demonstrated via single and multiple targets tracking simulations. In simulation, the target maneuver, the presence of clutter and the varying of parameters are taken into consideration. 展开更多
关键词 data association D S evidence inference theory data fusion
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