The characteristics of surface maneuver targets are analyzed and a 3-D relative motion model for missiles and targets is established. A variable structure guidance law is designed considering the characteristics of ta...The characteristics of surface maneuver targets are analyzed and a 3-D relative motion model for missiles and targets is established. A variable structure guidance law is designed considering the characteristics of targets. In the guidance law, the distance between missiles and targets as well as the missile-target relative velocity are all substituted by estimation values. The estimation errors, the target＇s velocity, and the maneuver acceleration are all treated as bounded disturbance. The guidance law proposed can be implemented conveniently in engineering with little target information. The performance of the guidance system is analyzed theoretically and the numerical simulation result shows the effectiveness of the guidance law.展开更多
To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle(USV)perception,this paper proposes a method based on the fusion of visual and...To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle(USV)perception,this paper proposes a method based on the fusion of visual and LiDAR point-cloud projection for water surface target detection.Firstly,the visual recognition component employs an improved YOLOv7 algorithmbased on a self-built dataset for the detection of water surface targets.This algorithm modifies the original YOLOv7 architecture to a Slim-Neck structure,addressing the problemof excessive redundant information during feature extraction in the original YOLOv7 network model.Simultaneously,this modification simplifies the computational burden of the detector,reduces inference time,and maintains accuracy.Secondly,to tackle the issue of sample imbalance in the self-built dataset,slide loss function is introduced.Finally,this paper replaces the original Complete Intersection over Union(CIoU)loss function with the Minimum Point Distance Intersection over Union(MPDIoU)loss function in the YOLOv7 algorithm,which accelerates model learning and enhances robustness.To mitigate the problem of missed recognitions caused by complex water surface conditions in purely visual algorithms,this paper further adopts the fusion of LiDAR and camera data,projecting the threedimensional point-cloud data from LiDAR onto a two-dimensional pixel plane.This significantly reduces the rate of missed detections for water surface targets.展开更多
To fulfill the need for acquiring three-dimensional(3D) objects with more realistic textures and depth information, this study proposes a method based on near-infrared laser, combined with dual camera field of view ce...To fulfill the need for acquiring three-dimensional(3D) objects with more realistic textures and depth information, this study proposes a method based on near-infrared laser, combined with dual camera field of view center correction and binocular stereo calibration, to precisely capture the target surface texture. Furthermore, we constructed a verification system using standard industrial cameras and line lasers, achieving the generation of binocular line laser point cloud real textures. Experiments conducted within a 400 mm to 600 mm testing range achieved a reconstruction accuracy of 0.047 2 mm and reduced the texture mapping error to 0.323 4 pixel, proving the effectiveness of this method and providing a high-precision, low-cost solution for 3D point cloud model texture mapping.展开更多
In this paper, we consider the problem of irregular shapes tracking for multiple extended targets by introducing the Gaussian surface matrix（GSM） into the framework of the random finite set（RFS） theory. The Gaussi...In this paper, we consider the problem of irregular shapes tracking for multiple extended targets by introducing the Gaussian surface matrix（GSM） into the framework of the random finite set（RFS） theory. The Gaussian surface function is constructed first by the measurements, and it is used to define the GSM via a mapping function. We then integrate the GSM with the probability hypothesis density（PHD） filter, the Bayesian recursion formulas of GSM-PHD are derived and the Gaussian mixture implementation is employed to obtain the closed-form solutions. Moreover, the estimated shapes are designed to guide the measurement set sub-partition, which can cope with the problem of the spatially close target tracking. Simulation results show that the proposed algorithm can effectively estimate irregular target shapes and exhibit good robustness in cross extended target tracking.展开更多
The traditional small target detection algorithm often results in a high false alarm rate on the sea surface background. To address this issue, a small target detection method based on guided filtering and local avera...The traditional small target detection algorithm often results in a high false alarm rate on the sea surface background. To address this issue, a small target detection method based on guided filtering and local average gray level difference was proposed in this paper for the sea surface. Firstly, the method enhanced the details of the small targets by employing guided filtering to suppress the background clutter and noise in the sea surface image. Subsequently, the local average gray level difference of each point in the image was calculated to further distinguish the targets from other interference points. Finally, the threshold segmentation method was utilized to obtain the actual small targets on the sea surface. After conducting experiments on various sea surface scenes, the LSCRG, BSF, and ROC curve were computed for the proposed method and five other algorithms. Comparative analysis with BS, Top-hat, TDLMS, Max-median, and LCM demonstrates the superiority of the proposed method for infrared small target detection on the sea surface.展开更多
The sea surface escort formation faces various threats in reality. For example, suicide boats may carry explosives or other dangerous items, aiming to cause maximum damage by colliding or detonating escort targets. Si...The sea surface escort formation faces various threats in reality. For example, suicide boats may carry explosives or other dangerous items, aiming to cause maximum damage by colliding or detonating escort targets. Since suicide boats have a certain degree of concealment, it is necessary to establish a threat assessment algorithm to timely identify and respond to such fast and concealed threats. This paper establishes a threat assessment model that considers the instantaneous and historical states of the target. The instantaneous state of the target takes into account six evaluation indicators, including target category, target distance, target heading, target speed, collision risk, and ship automatic identification system(AIS) recognition status;in terms of historical state information mining, a target typical intention recognition method based on graph neural network is proposed to achieve end-to-end target typical intention recognition. Furthermore, this paper introduces a multi-attribute decision analysis method to weight the evaluation indicators, improves the relative closeness calculation method between different evaluation schemes and positive and negative ideal schemes, and determines the target threat ranking based on relative closeness. Based on Unity3D, a set of unmanned boat confrontation simulation system is designed and developed, and typical intention recognition data sets and threat assessment scenario simulation data are generated through real-life confrontation. Comparative analysis shows that the threat assessment model in this paper can accurately and timely detect raid target threats and give scientific and reasonable target threat ranking results.展开更多
Surface/underwater target classification is a key topic in marine information research.However,the complex underwater environment,coupled with the diversity of target types and their variable characteristics,presents ...Surface/underwater target classification is a key topic in marine information research.However,the complex underwater environment,coupled with the diversity of target types and their variable characteristics,presents significant challenges for classifier design.For shallow-water waveguides with a negative thermocline,a residual neural network(ResNet)model based on the sound field elevation structure is constructed.This model demonstrates robust classification performance even when facing low signal-to-noise ratios and environmental mismatches.Meanwhile,to address the reduced generalization ability caused by limited labeled acoustic data,an improved ResNet model based on unsupervised domain adaptation(“proposed UDA-ResNet”)is further constructed.This model incorporates data on simulated elevation structures of the sound field to augment the training process.Adversarial training is employed to extract domain-invariant features from simulated and trial data.These strategies help reduce the negative impact caused by domain differences.Experimental results demonstrate that the proposed method shows strong surface/underwater target classification ability under limited sample sizes,thus confirming its feasibility and effectiveness.展开更多
Targeted-delivery is of great importance to molecular probes and drugs for cell biology study. Herein we reported 11 sulfur-containing coumarins as cell imaging probes. Different sulfur speciation of the 4 representat...Targeted-delivery is of great importance to molecular probes and drugs for cell biology study. Herein we reported 11 sulfur-containing coumarins as cell imaging probes. Different sulfur speciation of the 4 representative coumarins SC1-SC4 renders them significantly different subcellular localizations and cellular uptake pathways： SC1 containing thioether group located in lysosomes, while sulfoxide and sulfone compounds SC2 and SC3 distributed in the whole cell. Furthermore, the cationic sulfonium containing compound SC4 was internalized by clathrin-mediated endocytosis and localized at mitochondria. By analyzing the molecular parameters of all 11 coumarins, we found that different sulfur speciation affected their lipophilicity and electrostatic surface potential. These two key factors play roles in altering biological behaviors of the coumarins. The results revealed the importance of sulfur speciation on the physicochemical properties and thus subcellular localization of bioprobes. This is useful for designing new functional bioprobes.展开更多
文摘The characteristics of surface maneuver targets are analyzed and a 3-D relative motion model for missiles and targets is established. A variable structure guidance law is designed considering the characteristics of targets. In the guidance law, the distance between missiles and targets as well as the missile-target relative velocity are all substituted by estimation values. The estimation errors, the target＇s velocity, and the maneuver acceleration are all treated as bounded disturbance. The guidance law proposed can be implemented conveniently in engineering with little target information. The performance of the guidance system is analyzed theoretically and the numerical simulation result shows the effectiveness of the guidance law.
基金supported by the National Natural Science Foundation of China(No.51876114)the Shanghai Engineering Research Center of Marine Renewable Energy(Grant No.19DZ2254800).
文摘To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle(USV)perception,this paper proposes a method based on the fusion of visual and LiDAR point-cloud projection for water surface target detection.Firstly,the visual recognition component employs an improved YOLOv7 algorithmbased on a self-built dataset for the detection of water surface targets.This algorithm modifies the original YOLOv7 architecture to a Slim-Neck structure,addressing the problemof excessive redundant information during feature extraction in the original YOLOv7 network model.Simultaneously,this modification simplifies the computational burden of the detector,reduces inference time,and maintains accuracy.Secondly,to tackle the issue of sample imbalance in the self-built dataset,slide loss function is introduced.Finally,this paper replaces the original Complete Intersection over Union(CIoU)loss function with the Minimum Point Distance Intersection over Union(MPDIoU)loss function in the YOLOv7 algorithm,which accelerates model learning and enhances robustness.To mitigate the problem of missed recognitions caused by complex water surface conditions in purely visual algorithms,this paper further adopts the fusion of LiDAR and camera data,projecting the threedimensional point-cloud data from LiDAR onto a two-dimensional pixel plane.This significantly reduces the rate of missed detections for water surface targets.
基金supported by the Program for Innovative Research Team in University of Tianjin (No.TD13-5036)the Tianjin Science and Technology Popularization Project (No.22KPXMRC00090)。
文摘To fulfill the need for acquiring three-dimensional(3D) objects with more realistic textures and depth information, this study proposes a method based on near-infrared laser, combined with dual camera field of view center correction and binocular stereo calibration, to precisely capture the target surface texture. Furthermore, we constructed a verification system using standard industrial cameras and line lasers, achieving the generation of binocular line laser point cloud real textures. Experiments conducted within a 400 mm to 600 mm testing range achieved a reconstruction accuracy of 0.047 2 mm and reduced the texture mapping error to 0.323 4 pixel, proving the effectiveness of this method and providing a high-precision, low-cost solution for 3D point cloud model texture mapping.
基金supported by the National Natural Science Foundation of China(6130501761304264+1 种基金61402203)the Natural Science Foundation of Jiangsu Province(BK20130154)
文摘In this paper, we consider the problem of irregular shapes tracking for multiple extended targets by introducing the Gaussian surface matrix（GSM） into the framework of the random finite set（RFS） theory. The Gaussian surface function is constructed first by the measurements, and it is used to define the GSM via a mapping function. We then integrate the GSM with the probability hypothesis density（PHD） filter, the Bayesian recursion formulas of GSM-PHD are derived and the Gaussian mixture implementation is employed to obtain the closed-form solutions. Moreover, the estimated shapes are designed to guide the measurement set sub-partition, which can cope with the problem of the spatially close target tracking. Simulation results show that the proposed algorithm can effectively estimate irregular target shapes and exhibit good robustness in cross extended target tracking.
文摘The traditional small target detection algorithm often results in a high false alarm rate on the sea surface background. To address this issue, a small target detection method based on guided filtering and local average gray level difference was proposed in this paper for the sea surface. Firstly, the method enhanced the details of the small targets by employing guided filtering to suppress the background clutter and noise in the sea surface image. Subsequently, the local average gray level difference of each point in the image was calculated to further distinguish the targets from other interference points. Finally, the threshold segmentation method was utilized to obtain the actual small targets on the sea surface. After conducting experiments on various sea surface scenes, the LSCRG, BSF, and ROC curve were computed for the proposed method and five other algorithms. Comparative analysis with BS, Top-hat, TDLMS, Max-median, and LCM demonstrates the superiority of the proposed method for infrared small target detection on the sea surface.
基金funded by by the National Natural Science Foundation of China under Grant 52101377。
文摘The sea surface escort formation faces various threats in reality. For example, suicide boats may carry explosives or other dangerous items, aiming to cause maximum damage by colliding or detonating escort targets. Since suicide boats have a certain degree of concealment, it is necessary to establish a threat assessment algorithm to timely identify and respond to such fast and concealed threats. This paper establishes a threat assessment model that considers the instantaneous and historical states of the target. The instantaneous state of the target takes into account six evaluation indicators, including target category, target distance, target heading, target speed, collision risk, and ship automatic identification system(AIS) recognition status;in terms of historical state information mining, a target typical intention recognition method based on graph neural network is proposed to achieve end-to-end target typical intention recognition. Furthermore, this paper introduces a multi-attribute decision analysis method to weight the evaluation indicators, improves the relative closeness calculation method between different evaluation schemes and positive and negative ideal schemes, and determines the target threat ranking based on relative closeness. Based on Unity3D, a set of unmanned boat confrontation simulation system is designed and developed, and typical intention recognition data sets and threat assessment scenario simulation data are generated through real-life confrontation. Comparative analysis shows that the threat assessment model in this paper can accurately and timely detect raid target threats and give scientific and reasonable target threat ranking results.
基金supported by the National Natural Science Foundation of China(Grant Nos.62471024 and 62301183)the Open Research Fund of Hanjiang Laboratory(KF2024001).
文摘Surface/underwater target classification is a key topic in marine information research.However,the complex underwater environment,coupled with the diversity of target types and their variable characteristics,presents significant challenges for classifier design.For shallow-water waveguides with a negative thermocline,a residual neural network(ResNet)model based on the sound field elevation structure is constructed.This model demonstrates robust classification performance even when facing low signal-to-noise ratios and environmental mismatches.Meanwhile,to address the reduced generalization ability caused by limited labeled acoustic data,an improved ResNet model based on unsupervised domain adaptation(“proposed UDA-ResNet”)is further constructed.This model incorporates data on simulated elevation structures of the sound field to augment the training process.Adversarial training is employed to extract domain-invariant features from simulated and trial data.These strategies help reduce the negative impact caused by domain differences.Experimental results demonstrate that the proposed method shows strong surface/underwater target classification ability under limited sample sizes,thus confirming its feasibility and effectiveness.
基金financial support from the National Key Basic Research Support Foundation of China(No. 2015CB856301)the National Natural Scientific Foundation of China (Nos. 21571007, 21271013,21321001)
文摘Targeted-delivery is of great importance to molecular probes and drugs for cell biology study. Herein we reported 11 sulfur-containing coumarins as cell imaging probes. Different sulfur speciation of the 4 representative coumarins SC1-SC4 renders them significantly different subcellular localizations and cellular uptake pathways： SC1 containing thioether group located in lysosomes, while sulfoxide and sulfone compounds SC2 and SC3 distributed in the whole cell. Furthermore, the cationic sulfonium containing compound SC4 was internalized by clathrin-mediated endocytosis and localized at mitochondria. By analyzing the molecular parameters of all 11 coumarins, we found that different sulfur speciation affected their lipophilicity and electrostatic surface potential. These two key factors play roles in altering biological behaviors of the coumarins. The results revealed the importance of sulfur speciation on the physicochemical properties and thus subcellular localization of bioprobes. This is useful for designing new functional bioprobes.
