A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of...A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.展开更多
To objectively obtain the three-dimensional coordinates of the projectile fuze proximity explosion when projectile intersects the head of missile target, we propose a dynamic seven photoelectric detection screen test ...To objectively obtain the three-dimensional coordinates of the projectile fuze proximity explosion when projectile intersects the head of missile target, we propose a dynamic seven photoelectric detection screen test method, which is made up of six plane detection screens and a flash photoelectric dynamic detection screen. The three-dimensional coordinates calculation model of the projectile proximity explosion position based on seven plane detection screens with dynamic characteristics is established.According to the relation of the dynamic seven photoelectric detection screen planes and the time values,the analytical function of the projectile proximity explosion position parameters under non-linear motion is derived. The projectile signal filtering method based on discrete wavelet transform is explored in this work. Additionally, the projectile signal recognition algorithm using an improved particle swarm is proposed. Based on the characteristics of the time duration and the signal peak error for the projectile passing through the detection screen, the signals attribution of the same projectile passing through six detection screens are analyzed for obtaining precise time values of the same projectile passing through the detection screens. On the basis of the projectile fuze proximity explosion test, the linear motion model and the proposed non-linear motion model are used to calculate and compare the same group of projectiles proximity explosion position parameters. The comparison of test results verifies that the proposed test method and calculation model in this work accurately obtain the actual projectile proximity explosion position parameters.展开更多
Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobil...Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter(KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system(FIS), and the fuzzy adaptive Kalman filter(FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.展开更多
A compensation implementation scheme of the advanced targeting process based on the fine tracking system is proposed in this paper.Based on the working process of the quantum positioning system(QPS)and its acquisition...A compensation implementation scheme of the advanced targeting process based on the fine tracking system is proposed in this paper.Based on the working process of the quantum positioning system(QPS)and its acquisition,tracking and pointing(ATP)system,the advanced targeting subsystem of the ATP system is designed.Based on six orbital parameters of the quantum satellite Mozi,the advanced targeting azimuth angle and pitch angle are transformed into the dynamic tracking center of the fine tracking system in the ATP system.The deviation of the advanced targeting process is analyzed.In the Simulink,the simulation experiment of the ATP system considering the deviation compensation of the advanced targeting is carried out,and the results are analyzed.展开更多
Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the see...Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the seekers the FOV is not fully exploited which means the target can be missed before becoming out of the FOV,this results of the nonlinearity of the reticle structure.In this paper,a novel method of the target position detection a crossed four slits or crossed array trackers(CAT) seeker will be designed,simulated and evaluated.The idea of this method depends on dividing the FOV into main regions up to a certain parameter,which is the pulses number;then,each main region will be divided into sub-regions up to a second parameter which will be the pulses distribution a spin period.The errors sources will be discussed and evaluated.Other new idea will be applied which is exploiting some area of the FOV where a part of the position data is missed in the information signal by pushing the target to the region where the information signal carries the total position data.展开更多
针对印刷电路板(printed circuit board,PCB)缺陷检测过程中,因包含丰富的小目标缺陷,易出现漏检、误检现象,提出一种基于改进增强金字塔实时检测变换器(enhance pyramid real time detection transformer,EP-RTDETR)小目标PCB表面缺陷...针对印刷电路板(printed circuit board,PCB)缺陷检测过程中,因包含丰富的小目标缺陷,易出现漏检、误检现象,提出一种基于改进增强金字塔实时检测变换器(enhance pyramid real time detection transformer,EP-RTDETR)小目标PCB表面缺陷检测算法。首先,使用CSPDarknet替代原始骨干网络,以增强模型的特征提取能力;其次,设空间移动卷积门控线性单元(spatial moving point convolutional gated linear unit,SMPCGLU)模块改造C2f中的Bottleneck,增强了特征的门控调制能力和空间自适应性;再次,引入可学习位置编码,改进尺度交互机制,增强对不同位置信息的响应能力;然后,基于跨尺度特征融合模块(cross-scale feature-fusion module,CCFM)模块设计小目标增强金字塔结构(small object enhance pyramid,SOEP),增强的特征层和精细的特征融合使模型能够更准确地定位和识别小目标;最后,设计MPDIoU(minimum point distance-based intersection over union)+NWD(normalized wasserstein distance)loss,在加快模型收敛速度的同时更加关注小目标缺陷,回归结果更加准确。试验结果表明,相较于基准模型,准确率P提高了4.6%,召回率R提高了5.1%,平均精度均值mAP50提高了4.6%,参数量减少了16.38 M,浮点数减少了48.3,FPS提高了8.51 s,能够更好地进行小目标PCB表面缺陷检测。展开更多
文摘A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.
基金supported by Project of the National Natural Science Foundation of China (No.62073256, 61773305)the Key Science and Technology Program of Shaanxi Province (No.2020GY-125)Xi’an Science and Technology Innovation talent service enterprise project (No.2020KJRC0041)。
文摘To objectively obtain the three-dimensional coordinates of the projectile fuze proximity explosion when projectile intersects the head of missile target, we propose a dynamic seven photoelectric detection screen test method, which is made up of six plane detection screens and a flash photoelectric dynamic detection screen. The three-dimensional coordinates calculation model of the projectile proximity explosion position based on seven plane detection screens with dynamic characteristics is established.According to the relation of the dynamic seven photoelectric detection screen planes and the time values,the analytical function of the projectile proximity explosion position parameters under non-linear motion is derived. The projectile signal filtering method based on discrete wavelet transform is explored in this work. Additionally, the projectile signal recognition algorithm using an improved particle swarm is proposed. Based on the characteristics of the time duration and the signal peak error for the projectile passing through the detection screen, the signals attribution of the same projectile passing through six detection screens are analyzed for obtaining precise time values of the same projectile passing through the detection screens. On the basis of the projectile fuze proximity explosion test, the linear motion model and the proposed non-linear motion model are used to calculate and compare the same group of projectiles proximity explosion position parameters. The comparison of test results verifies that the proposed test method and calculation model in this work accurately obtain the actual projectile proximity explosion position parameters.
基金Project(2013AA06A411)supported by the National High Technology Research and Development Program of ChinaProject(CXZZ14_1374)supported by the Graduate Education Innovation Program of Jiangsu Province,ChinaProject supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions,China
文摘Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter(KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system(FIS), and the fuzzy adaptive Kalman filter(FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.
基金supported by the National Natural Science Foundation of China(61973290).
文摘A compensation implementation scheme of the advanced targeting process based on the fine tracking system is proposed in this paper.Based on the working process of the quantum positioning system(QPS)and its acquisition,tracking and pointing(ATP)system,the advanced targeting subsystem of the ATP system is designed.Based on six orbital parameters of the quantum satellite Mozi,the advanced targeting azimuth angle and pitch angle are transformed into the dynamic tracking center of the fine tracking system in the ATP system.The deviation of the advanced targeting process is analyzed.In the Simulink,the simulation experiment of the ATP system considering the deviation compensation of the advanced targeting is carried out,and the results are analyzed.
文摘Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the seekers the FOV is not fully exploited which means the target can be missed before becoming out of the FOV,this results of the nonlinearity of the reticle structure.In this paper,a novel method of the target position detection a crossed four slits or crossed array trackers(CAT) seeker will be designed,simulated and evaluated.The idea of this method depends on dividing the FOV into main regions up to a certain parameter,which is the pulses number;then,each main region will be divided into sub-regions up to a second parameter which will be the pulses distribution a spin period.The errors sources will be discussed and evaluated.Other new idea will be applied which is exploiting some area of the FOV where a part of the position data is missed in the information signal by pushing the target to the region where the information signal carries the total position data.
文摘针对印刷电路板(printed circuit board,PCB)缺陷检测过程中,因包含丰富的小目标缺陷,易出现漏检、误检现象,提出一种基于改进增强金字塔实时检测变换器(enhance pyramid real time detection transformer,EP-RTDETR)小目标PCB表面缺陷检测算法。首先,使用CSPDarknet替代原始骨干网络,以增强模型的特征提取能力;其次,设空间移动卷积门控线性单元(spatial moving point convolutional gated linear unit,SMPCGLU)模块改造C2f中的Bottleneck,增强了特征的门控调制能力和空间自适应性;再次,引入可学习位置编码,改进尺度交互机制,增强对不同位置信息的响应能力;然后,基于跨尺度特征融合模块(cross-scale feature-fusion module,CCFM)模块设计小目标增强金字塔结构(small object enhance pyramid,SOEP),增强的特征层和精细的特征融合使模型能够更准确地定位和识别小目标;最后,设计MPDIoU(minimum point distance-based intersection over union)+NWD(normalized wasserstein distance)loss,在加快模型收敛速度的同时更加关注小目标缺陷,回归结果更加准确。试验结果表明,相较于基准模型,准确率P提高了4.6%,召回率R提高了5.1%,平均精度均值mAP50提高了4.6%,参数量减少了16.38 M,浮点数减少了48.3,FPS提高了8.51 s,能够更好地进行小目标PCB表面缺陷检测。
