In challenging situations,such as low illumination,rain,and background clutter,the stability of the thermal infrared(TIR)spectrum can help red,green,blue(RGB)visible spectrum to improve tracking performance.However,th...In challenging situations,such as low illumination,rain,and background clutter,the stability of the thermal infrared(TIR)spectrum can help red,green,blue(RGB)visible spectrum to improve tracking performance.However,the high-level image information and the modality-specific features have not been sufficiently studied.The proposed correlation filter uses the fused saliency content map to improve filter training and extracts different features of modalities.The fused content map is intro-duced into the spatial regularization term of correlation filter to highlight the training samples in the content region.Furthermore,the fused content map can avoid the incompleteness of the con-tent region caused by challenging situations.Additionally,differ-ent features are extracted according to the modality characteris-tics and are fused by the designed response-level fusion stra-tegy.The alternating direction method of multipliers(ADMM)algorithm is used to solve the tracker training efficiently.Experi-ments on the large-scale benchmark datasets show the effec-tiveness of the proposed tracker compared to the state-of-the-art traditional trackers and the deep learning based trackers.展开更多
Annular grooved projectiles(AGPs)have drawn ongoing concerns as an advanced penetrator for their excellent anti-rebound capability in impacting metal plates.They could become embedded solidly in the target surface dur...Annular grooved projectiles(AGPs)have drawn ongoing concerns as an advanced penetrator for their excellent anti-rebound capability in impacting metal plates.They could become embedded solidly in the target surface during low-velocity impact.In this investigation,the firm embedding behavior of AGP was observed by impact experiments.Corresponding numerical simulations provided a better understanding of this process.Experimental and numerical results indicated that the firm embedding behavior of AGP was mainly due to the filling-material in the groove rather than the friction between the projectile and target,unlike traditional shape such as conical projectile.According to observation,firm embedding process can generally be subdivided into four stages:initial-cratering stage,groove-filling stage,fillingmaterial failure stage and rebound vibration stage.Moreover,the damage mechanics of target material around crater was obtained through microscopic tests.A comparison of the cross-sectional figures between the experiment and simulation proved that the analysis and the proposed method were reasonable and feasible,which further demonstrated that the firm embedding behavior has application potential in new concept warheads.展开更多
A hierarchical particle filter（HPF） framework based on multi-feature fusion is proposed.The proposed HPF effectively uses different feature information to avoid the tracking failure based on the single feature in a ...A hierarchical particle filter（HPF） framework based on multi-feature fusion is proposed.The proposed HPF effectively uses different feature information to avoid the tracking failure based on the single feature in a complicated environment.In this approach,the Harris algorithm is introduced to detect the corner points of the object,and the corner matching algorithm based on singular value decomposition is used to compute the firstorder weights and make particles centralize in the high likelihood area.Then the local binary pattern（LBP） operator is used to build the observation model of the target based on the color and texture features,by which the second-order weights of particles and the accurate location of the target can be obtained.Moreover,a backstepping controller is proposed to complete the whole tracking system.Simulations and experiments are carried out,and the results show that the HPF algorithm with the backstepping controller achieves stable and accurate tracking with good robustness in complex environments.展开更多
The evolution of airborne tactical networks(ATNs)is impeded by the network ossification problem.As a solution,network virtualization(NV)can provide a flexible and scalable architecture where virtual network embedding(...The evolution of airborne tactical networks(ATNs)is impeded by the network ossification problem.As a solution,network virtualization(NV)can provide a flexible and scalable architecture where virtual network embedding(VNE)is a key part.However,existing VNE algorithms cannot be optimally adopted in the virtualization of ATN due to the complex interference in aircombat field.In this context,a highly reliable VNE algorithm based on the transmission rate for ATN virtualization(TR-ATVNE)is proposed to adapt well to the specific electromagnetic environment of ATN.Our algorithm coordinates node and link mapping.In the node mapping,transmission-rate resource is firstly defined to effectively evaluate the ranking value of substrate nodes under the interference of both environmental noises and enemy attacks.Meanwhile,a feasible splitting rule is proposed for path splitting in the link mapping,considering the interference between wireless links.Simulation results reveal that our algorithm is able to improve the acceptance ratio of virtual network requests while maintaining a high revenue-to-cost ratio under the complex electromagnetic interference.展开更多
Link prediction of combat networks is of significant military value for precisely identifying the vital infrastructure of the enemy target and optimizing the operational plan of our side.Due to the profound uncertaint...Link prediction of combat networks is of significant military value for precisely identifying the vital infrastructure of the enemy target and optimizing the operational plan of our side.Due to the profound uncertainty in the battleground circumstances, the acquired topological information of the opponent combat network always presents sparse characteristics. To solve this problem, a novel approach named network embedding based combat network link prediction(NECLP) is put forward to predict missing links of sparse combat networks. First,node embedding techniques are presented to preserve as much information of the combat network as possible using a low-dimensional space. Then, we put forward a solution algorithm to predict links between combat networks based on node embedding similarity. Last, massive experiments are carried out on a real-world combat network case to verify the validity and practicality of the proposed NECLP. This paper compares six baseline methods, and experimental results show that the NECLP has outstanding performance and substantially outperforms the baseline methods.展开更多
基金supported by the National Natural Science Foundation of China(62073036,62076031)Beijing Natural Science Foundation(4242049).
文摘In challenging situations,such as low illumination,rain,and background clutter,the stability of the thermal infrared(TIR)spectrum can help red,green,blue(RGB)visible spectrum to improve tracking performance.However,the high-level image information and the modality-specific features have not been sufficiently studied.The proposed correlation filter uses the fused saliency content map to improve filter training and extracts different features of modalities.The fused content map is intro-duced into the spatial regularization term of correlation filter to highlight the training samples in the content region.Furthermore,the fused content map can avoid the incompleteness of the con-tent region caused by challenging situations.Additionally,differ-ent features are extracted according to the modality characteris-tics and are fused by the designed response-level fusion stra-tegy.The alternating direction method of multipliers(ADMM)algorithm is used to solve the tracker training efficiently.Experi-ments on the large-scale benchmark datasets show the effec-tiveness of the proposed tracker compared to the state-of-the-art traditional trackers and the deep learning based trackers.
基金financially supported by the National Natural Science Foundation of China [grant number 11472053]
文摘Annular grooved projectiles(AGPs)have drawn ongoing concerns as an advanced penetrator for their excellent anti-rebound capability in impacting metal plates.They could become embedded solidly in the target surface during low-velocity impact.In this investigation,the firm embedding behavior of AGP was observed by impact experiments.Corresponding numerical simulations provided a better understanding of this process.Experimental and numerical results indicated that the firm embedding behavior of AGP was mainly due to the filling-material in the groove rather than the friction between the projectile and target,unlike traditional shape such as conical projectile.According to observation,firm embedding process can generally be subdivided into four stages:initial-cratering stage,groove-filling stage,fillingmaterial failure stage and rebound vibration stage.Moreover,the damage mechanics of target material around crater was obtained through microscopic tests.A comparison of the cross-sectional figures between the experiment and simulation proved that the analysis and the proposed method were reasonable and feasible,which further demonstrated that the firm embedding behavior has application potential in new concept warheads.
基金supported by the National Natural Science Foundation of China(61304097)the Projects of Major International(Regional)Joint Research Program NSFC(61120106010)the Foundation for Innovation Research Groups of the National National Natural Science Foundation of China(61321002)
文摘A hierarchical particle filter（HPF） framework based on multi-feature fusion is proposed.The proposed HPF effectively uses different feature information to avoid the tracking failure based on the single feature in a complicated environment.In this approach,the Harris algorithm is introduced to detect the corner points of the object,and the corner matching algorithm based on singular value decomposition is used to compute the firstorder weights and make particles centralize in the high likelihood area.Then the local binary pattern（LBP） operator is used to build the observation model of the target based on the color and texture features,by which the second-order weights of particles and the accurate location of the target can be obtained.Moreover,a backstepping controller is proposed to complete the whole tracking system.Simulations and experiments are carried out,and the results show that the HPF algorithm with the backstepping controller achieves stable and accurate tracking with good robustness in complex environments.
基金supported by the National Natural Science Foundation of China(61701521)the Shaanxi Provincial Natural Science Foundation(2018JQ6074)。
文摘The evolution of airborne tactical networks(ATNs)is impeded by the network ossification problem.As a solution,network virtualization(NV)can provide a flexible and scalable architecture where virtual network embedding(VNE)is a key part.However,existing VNE algorithms cannot be optimally adopted in the virtualization of ATN due to the complex interference in aircombat field.In this context,a highly reliable VNE algorithm based on the transmission rate for ATN virtualization(TR-ATVNE)is proposed to adapt well to the specific electromagnetic environment of ATN.Our algorithm coordinates node and link mapping.In the node mapping,transmission-rate resource is firstly defined to effectively evaluate the ranking value of substrate nodes under the interference of both environmental noises and enemy attacks.Meanwhile,a feasible splitting rule is proposed for path splitting in the link mapping,considering the interference between wireless links.Simulation results reveal that our algorithm is able to improve the acceptance ratio of virtual network requests while maintaining a high revenue-to-cost ratio under the complex electromagnetic interference.
基金supported by the National Natural Science Foundation of China (7190121271971213)。
文摘Link prediction of combat networks is of significant military value for precisely identifying the vital infrastructure of the enemy target and optimizing the operational plan of our side.Due to the profound uncertainty in the battleground circumstances, the acquired topological information of the opponent combat network always presents sparse characteristics. To solve this problem, a novel approach named network embedding based combat network link prediction(NECLP) is put forward to predict missing links of sparse combat networks. First,node embedding techniques are presented to preserve as much information of the combat network as possible using a low-dimensional space. Then, we put forward a solution algorithm to predict links between combat networks based on node embedding similarity. Last, massive experiments are carried out on a real-world combat network case to verify the validity and practicality of the proposed NECLP. This paper compares six baseline methods, and experimental results show that the NECLP has outstanding performance and substantially outperforms the baseline methods.
基金国家自然科学基金联合基金项目(U21A20485)浙江省高等教育“十四五”本科教育教学改革项目(jg20220019)+3 种基金浙江省产学合作协同育人项目(202018)浙江大学2023年度本科教学创新实践项目重点项目(202309)浙江省基础公益研究计划项目(LGG22F030008)浙江大学第一批AI For Education系列实证教学研究项目(202402)。
