With the great development of Multi-Target Tracking(MTT)technologies,many MTT algorithms have been proposed with their own advantages and disadvantages.Due to the fact that requirements to MTT algorithms vary from the...With the great development of Multi-Target Tracking(MTT)technologies,many MTT algorithms have been proposed with their own advantages and disadvantages.Due to the fact that requirements to MTT algorithms vary from the application scenarios,performance evaluation is significant to select an appropriate MTT algorithm for the specific application scenario.In this paper,we propose a performance evaluation method on the sets of trajectories with temporal dimension specifics to compare the estimated trajectories with the true trajectories.The proposed method evaluates the estimate results of an MTT algorithm in terms of tracking accuracy,continuity and clarity.Furthermore,its computation is based on a multi-dimensional assignment problem,which is formulated as a computable form using linear programming.To enhance the influence of recent estimated states of the trajectories in the evaluation,an attention function is used to reweight the trajectory errors at different time steps.Finally,simulation results show that the proposed performance evaluation method is able to evaluate many aspects of the MTT algorithms.These evaluations are worthy for selecting suitable MTT algorithms in different application scenarios.展开更多
Rubber-based composites based on ethylene propylene diene monomer(EPDM)with excellent non-linear electrical conductivity are preferred to serve as reinforced insu-lation in cable accessories,which can self-adaptively ...Rubber-based composites based on ethylene propylene diene monomer(EPDM)with excellent non-linear electrical conductivity are preferred to serve as reinforced insu-lation in cable accessories,which can self-adaptively regulate electric field distribution and avoid electric field concentration due to the non-linear conductivity.The conductive carbon nanotubes(CNT)are filled into EPDM to improve the non-linear conductivity,while the insulating hexagonal boron nitride nanosheets(h-BN)are used to reconcile the electric breakdown strength.The results show that with the increase of CNT loading content,the non-linear conductivity of CNT/h-BN/EPDM com-posites becomes more prominent,accompanying the decrease of threshold field strength and increase of non-linear coefficient.However,the electric breakdown strength of CNT/h-BN/EPDM composites seriously deteriorates due to the increase of CNT content and temperature.By incorporating 10 wt.%h-BN into the com-posites,the reduction percentage of breakdown strength can be significantly lowered,which is 19.95%of neat EPDM and 13.74%of CNT/h-BN/EPDM composites at 70℃,respectively.The COMSOL Multiphysics simulation results demonstrate that using the CNT/h-BN/EPDM composite as the reinforced insulation can eliminate the electric field concentration of the cable accessory as well as enable the cable accessory with good lightning shock resistance.展开更多
The coalescence and missed detection are two key challenges in Multi-Target Tracking(MTT).To balance the tracking accuracy and real-time performance,the existing Random Finite Set(RFS)based filters are generally diffi...The coalescence and missed detection are two key challenges in Multi-Target Tracking(MTT).To balance the tracking accuracy and real-time performance,the existing Random Finite Set(RFS)based filters are generally difficult to handle the above problems simultaneously,such as the Track-Oriented marginal Multi-Bernoulli/Poisson(TOMB/P)and Measurement-Oriented marginal Multi-Bernoulli/Poisson(MOMB/P)filters.Based on the Arithmetic Average(AA)fusion rule,this paper proposes a novel fusion framework for the Poisson Multi-Bernoulli(PMB)filter,which integrates both the advantages of the TOMB/P filter in dealing with missed detection and the advantages of the MOMB/P filter in dealing with coalescence.In order to fuse the different PMB distributions,the Bernoulli components in different Multi-Bernoulli(MB)distributions are associated with each other by Kullback-Leibler Divergence(KLD)minimization.Moreover,an adaptive AA fusion rule is designed on the basis of the exponential fusion weights,which utilizes the TOMB/P and MOMB/P updates to solve these difficulties in MTT.Finally,by comparing with the TOMB/P and MOMB/P filters,the performance of the proposed filter in terms of accuracy and efficiency is demonstrated in three challenging scenarios.展开更多
Antiferroelectric PbZrO_(3)(AFE PZO)films have great potential to be used as the energy storage dielectrics due to the unique electric field(E)-induced phase transition character.However,the phase transition process a...Antiferroelectric PbZrO_(3)(AFE PZO)films have great potential to be used as the energy storage dielectrics due to the unique electric field(E)-induced phase transition character.However,the phase transition process always accompanies a polarization(P)hysteresis effect that induces the large energy loss(Wloss)and lowers the breakdown strength(EBDS),leading to the inferior energy storage density(Wrec)as well as low efficiency.In this work,the synergistic strategies by doping smaller ions of Li^(+)–Al^(3+)to substitute Pb2+and lowering the annealing temperature(T)from 700 to 550℃are proposed to change the microstructures and tune the polarization characters of PZO films,except to dramatically improve the energy storage performances.The prepared Pb_((1−x))(Li_(0.5)Al_(0.5))_(x)ZrO_(3)(P_((1−x))(L_(0.5)A_(0.5))_(x)ZO)films exhibit ferroelectric(FE)-like rather than AFE character once the doping content of Li^(+)–Al^(3+)ions reaches 6 mol%,accompanying a significant improvement of W_(rec) of 49.09 J/cm^(3),but the energy storage efficiency(η)is only 47.94%due to the long-correlation of FE domains.Accordingly,the low-temperature annealing is carried out to reduce the crystalline degree and the P loss.P_(0.94)(L_(0.5)A_(0.5))_(0.06)ZO films annealed at 550℃deliver a linear-like polarization behavior rather than FE-like behavior annealed at 700℃,and the lowered remanent polarization(P_(r))as well as improved E_(BDS)(4814 kV/cm)results in the superior Wrec of 58.7 J/cm^(3) and efficiency of 79.16%,simultaneously possessing excellent frequency and temperature stability and good electric fatigue tolerance.展开更多
Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In ...Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In this paper,considering the model-free purpose,we present an online Multi-Target Intelligent Tracking(MTIT)algorithm based on a Deep Long-Short Term Memory(DLSTM)network for complex tracking requirements,named the MTIT-DLSTM algorithm.Firstly,to distinguish trajectories and concatenate the tracking task in a time sequence,we define a target tuple set that is the labeled Random Finite Set(RFS).Then,prediction and update blocks based on the DLSTM network are constructed to predict and estimate the state of targets,respectively.Further,the prediction block can learn the movement trend from the historical state sequence,while the update block can capture the noise characteristic from the historical measurement sequence.Finally,a data association scheme based on Hungarian algorithm and the heuristic track management strategy are employed to assign measurements to targets and adapt births and deaths.Experimental results manifest that,compared with the existing tracking algorithms,our proposed MTIT-DLSTM algorithm can improve effectively the accuracy and robustness in estimating the state of targets appearing at random positions,and be applied to linear and nonlinear multi-target tracking scenarios.展开更多
0 INTRODUCTION Landslides occur globally and frequently,which often cause huge casualties and property losses(Cui et al.,2021).Therefore,landslide prevention is critical and challenging.Anchored slide-resistant piles ...0 INTRODUCTION Landslides occur globally and frequently,which often cause huge casualties and property losses(Cui et al.,2021).Therefore,landslide prevention is critical and challenging.Anchored slide-resistant piles are an effective support structure for a landslide with a thick sliding mass or strong thrust(Kang et al.,2009).展开更多
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
In the classical form,the Poisson Multi-Bernoulli Mixture(PMBM)filter uses a PMBM density to describe target birth,surviving,and death,which does not model the appearance of spawned targets.Although such a model can h...In the classical form,the Poisson Multi-Bernoulli Mixture(PMBM)filter uses a PMBM density to describe target birth,surviving,and death,which does not model the appearance of spawned targets.Although such a model can handle target birth,surviving,and death well,its performance may degrade when target spawning arises.The reason for this is that the original PMBM filter treats the spawned targets as birth targets,ignoring the surviving targets’information.In this paper,we propose a Kullback–Leibler Divergence(KLD)minimization based derivation for the PMBM prediction step,including target spawning,in which the spawned targets are modeled using a Poisson Point Process(PPP).Furthermore,to improve the computational efficiency,three approximations are used to implement the proposed algorithm,such as the Variational MultiBernoulli(VMB)filter,the Measurement-Oriented marginal MeMBer/Poisson(MOMB/P)filter,and the Track-Oriented marginal MeMBer/Poisson(TOMB/P)filter.Finally,simulation results demonstrate the validity of the proposed filter by using the spawning model in these three approximations.展开更多
基金supported by the National Natural Science Foundation of China(No.62276204,No.62306222)the Natural Science Basic Research Program of Shaanxi,China(No.2023-JC-QN-0710)。
文摘With the great development of Multi-Target Tracking(MTT)technologies,many MTT algorithms have been proposed with their own advantages and disadvantages.Due to the fact that requirements to MTT algorithms vary from the application scenarios,performance evaluation is significant to select an appropriate MTT algorithm for the specific application scenario.In this paper,we propose a performance evaluation method on the sets of trajectories with temporal dimension specifics to compare the estimated trajectories with the true trajectories.The proposed method evaluates the estimate results of an MTT algorithm in terms of tracking accuracy,continuity and clarity.Furthermore,its computation is based on a multi-dimensional assignment problem,which is formulated as a computable form using linear programming.To enhance the influence of recent estimated states of the trajectories in the evaluation,an attention function is used to reweight the trajectory errors at different time steps.Finally,simulation results show that the proposed performance evaluation method is able to evaluate many aspects of the MTT algorithms.These evaluations are worthy for selecting suitable MTT algorithms in different application scenarios.
基金National Natural Science Foundation of China,Grant/Award Numbers:U20A20308,52277024Heilongjiang Provincial Natural Science Foundation of China,Grant/Award Number:LH2020E093。
文摘Rubber-based composites based on ethylene propylene diene monomer(EPDM)with excellent non-linear electrical conductivity are preferred to serve as reinforced insu-lation in cable accessories,which can self-adaptively regulate electric field distribution and avoid electric field concentration due to the non-linear conductivity.The conductive carbon nanotubes(CNT)are filled into EPDM to improve the non-linear conductivity,while the insulating hexagonal boron nitride nanosheets(h-BN)are used to reconcile the electric breakdown strength.The results show that with the increase of CNT loading content,the non-linear conductivity of CNT/h-BN/EPDM com-posites becomes more prominent,accompanying the decrease of threshold field strength and increase of non-linear coefficient.However,the electric breakdown strength of CNT/h-BN/EPDM composites seriously deteriorates due to the increase of CNT content and temperature.By incorporating 10 wt.%h-BN into the com-posites,the reduction percentage of breakdown strength can be significantly lowered,which is 19.95%of neat EPDM and 13.74%of CNT/h-BN/EPDM composites at 70℃,respectively.The COMSOL Multiphysics simulation results demonstrate that using the CNT/h-BN/EPDM composite as the reinforced insulation can eliminate the electric field concentration of the cable accessory as well as enable the cable accessory with good lightning shock resistance.
基金supported by the National Natural Science Foundation of China(No.61871301)。
文摘The coalescence and missed detection are two key challenges in Multi-Target Tracking(MTT).To balance the tracking accuracy and real-time performance,the existing Random Finite Set(RFS)based filters are generally difficult to handle the above problems simultaneously,such as the Track-Oriented marginal Multi-Bernoulli/Poisson(TOMB/P)and Measurement-Oriented marginal Multi-Bernoulli/Poisson(MOMB/P)filters.Based on the Arithmetic Average(AA)fusion rule,this paper proposes a novel fusion framework for the Poisson Multi-Bernoulli(PMB)filter,which integrates both the advantages of the TOMB/P filter in dealing with missed detection and the advantages of the MOMB/P filter in dealing with coalescence.In order to fuse the different PMB distributions,the Bernoulli components in different Multi-Bernoulli(MB)distributions are associated with each other by Kullback-Leibler Divergence(KLD)minimization.Moreover,an adaptive AA fusion rule is designed on the basis of the exponential fusion weights,which utilizes the TOMB/P and MOMB/P updates to solve these difficulties in MTT.Finally,by comparing with the TOMB/P and MOMB/P filters,the performance of the proposed filter in terms of accuracy and efficiency is demonstrated in three challenging scenarios.
基金supported by the National Natural Science Foundation of China(Nos.52277024,U20A20308,and 51977050)Heilongjiang Provincial Natural Science Foundation of China(No.ZD2020E009)+3 种基金China Postdoctoral Science Foundation(Nos.2021T140166 and 2018M640303)Heilongjiang Province Postdoctoral Science Foundation(No.LBH-Z18099)University Nursing Program for Young Scholars with Creative Talents in Heilongjiang(No.UNPYSCT-2020178)Tiandong Zhang acknowledges the supports from China Scholarship Council(CSC)and China Association for Science and Technology.
文摘Antiferroelectric PbZrO_(3)(AFE PZO)films have great potential to be used as the energy storage dielectrics due to the unique electric field(E)-induced phase transition character.However,the phase transition process always accompanies a polarization(P)hysteresis effect that induces the large energy loss(Wloss)and lowers the breakdown strength(EBDS),leading to the inferior energy storage density(Wrec)as well as low efficiency.In this work,the synergistic strategies by doping smaller ions of Li^(+)–Al^(3+)to substitute Pb2+and lowering the annealing temperature(T)from 700 to 550℃are proposed to change the microstructures and tune the polarization characters of PZO films,except to dramatically improve the energy storage performances.The prepared Pb_((1−x))(Li_(0.5)Al_(0.5))_(x)ZrO_(3)(P_((1−x))(L_(0.5)A_(0.5))_(x)ZO)films exhibit ferroelectric(FE)-like rather than AFE character once the doping content of Li^(+)–Al^(3+)ions reaches 6 mol%,accompanying a significant improvement of W_(rec) of 49.09 J/cm^(3),but the energy storage efficiency(η)is only 47.94%due to the long-correlation of FE domains.Accordingly,the low-temperature annealing is carried out to reduce the crystalline degree and the P loss.P_(0.94)(L_(0.5)A_(0.5))_(0.06)ZO films annealed at 550℃deliver a linear-like polarization behavior rather than FE-like behavior annealed at 700℃,and the lowered remanent polarization(P_(r))as well as improved E_(BDS)(4814 kV/cm)results in the superior Wrec of 58.7 J/cm^(3) and efficiency of 79.16%,simultaneously possessing excellent frequency and temperature stability and good electric fatigue tolerance.
基金supported by the National Natural Science Foundation of China(No.62276204)Open Foundation of Science and Technology on Electronic Information Control Laboratory,Natural Science Basic Research Program of Shanxi,China(Nos.2022JM-340 and 2023-JC-QN-0710)China Postdoctoral Science Foundation(Nos.2020T130494 and 2018M633470).
文摘Multi-target tracking is facing the difficulties of modeling uncertain motion and observation noise.Traditional tracking algorithms are limited by specific models and priors that may mismatch a real-world scenario.In this paper,considering the model-free purpose,we present an online Multi-Target Intelligent Tracking(MTIT)algorithm based on a Deep Long-Short Term Memory(DLSTM)network for complex tracking requirements,named the MTIT-DLSTM algorithm.Firstly,to distinguish trajectories and concatenate the tracking task in a time sequence,we define a target tuple set that is the labeled Random Finite Set(RFS).Then,prediction and update blocks based on the DLSTM network are constructed to predict and estimate the state of targets,respectively.Further,the prediction block can learn the movement trend from the historical state sequence,while the update block can capture the noise characteristic from the historical measurement sequence.Finally,a data association scheme based on Hungarian algorithm and the heuristic track management strategy are employed to assign measurements to targets and adapt births and deaths.Experimental results manifest that,compared with the existing tracking algorithms,our proposed MTIT-DLSTM algorithm can improve effectively the accuracy and robustness in estimating the state of targets appearing at random positions,and be applied to linear and nonlinear multi-target tracking scenarios.
基金supported by the National Key R&D Program of China(Nos.2017YFC1501304 and 2018YFC1507200)the National Natural Science Foundation of China(Nos.42090054,41922055,41931295,42107181)+2 种基金the Key Research and Development Program of Hubei Province of China(No.2020BCB079)the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)(No.CUGGC09)the Research Project of China Three Gorges Corporation(No.2019073)。
文摘0 INTRODUCTION Landslides occur globally and frequently,which often cause huge casualties and property losses(Cui et al.,2021).Therefore,landslide prevention is critical and challenging.Anchored slide-resistant piles are an effective support structure for a landslide with a thick sliding mass or strong thrust(Kang et al.,2009).
基金supported by the National Natural Science Foundation of China(No.61871301)National Natural Science Foundation of Shaanxi Province,China(No.2018JQ6059)Postdoctoral Science Foundation of China(No.2018M633470)。
文摘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.
基金supported by the National Natural Science Foundation of China(No.61871301)。
文摘In the classical form,the Poisson Multi-Bernoulli Mixture(PMBM)filter uses a PMBM density to describe target birth,surviving,and death,which does not model the appearance of spawned targets.Although such a model can handle target birth,surviving,and death well,its performance may degrade when target spawning arises.The reason for this is that the original PMBM filter treats the spawned targets as birth targets,ignoring the surviving targets’information.In this paper,we propose a Kullback–Leibler Divergence(KLD)minimization based derivation for the PMBM prediction step,including target spawning,in which the spawned targets are modeled using a Poisson Point Process(PPP).Furthermore,to improve the computational efficiency,three approximations are used to implement the proposed algorithm,such as the Variational MultiBernoulli(VMB)filter,the Measurement-Oriented marginal MeMBer/Poisson(MOMB/P)filter,and the Track-Oriented marginal MeMBer/Poisson(TOMB/P)filter.Finally,simulation results demonstrate the validity of the proposed filter by using the spawning model in these three approximations.
