2024

• Record 13 of
  
  Title:Image motion compensation control method for the dynamic scan and stare imaging system
  
  Author Full Names:Gao, Peng; Su, Xiuqin; Pan, Zhibin; Liu, Ruoyu; Zhang, Wenbo; Cao, Yu; Wang, Lin

  Source Title:APPLIED OPTICS

  Language:English

  Document Type:Article

  Keywords Plus:STABILIZATION

  Abstract:The main function of the dynamic scan and stare imaging system is to quickly and continuously search a large area and perform high-resolution imaging. To eliminate image motion during the scanning process, this paper proposes an image motion compensation control method with dual-channel control. First, an improved model-assisted active disturbance rejection control is proposed, in which an auxiliary model is integrated into the algorithm to improve the control accuracy and response speed of the rotation rate of the platform. Second, a fast steering mirror (FSM) is introduced into the control system to compensate for the scanning speed and multiple disturbances. By adopting the amplitude frequency characteristics of the tracking differentiator, a parallel tracking differentiator filter is designed to suppress the interference of gyroscope noise on the FSM. When the system is disturbed by multiple frequency disturbances, the residual error of the image motion compensation is less than the spatial angular resolution of one pixel through the dual-channel stable control of the platform and the FSM. In the scan imaging experiment results, the average value of the grayscale variance function for the compensated images is close to 90% that of the static reference images. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

  Addresses:[Gao, Peng; Su, Xiuqin; Liu, Ruoyu; Zhang, Wenbo; Cao, Yu] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710000, Peoples R China; [Gao, Peng; Pan, Zhibin] Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian 710000, Peoples R China; [Gao, Peng] Univ Chinese Acad Sci, Beijing 100000, Peoples R China; [Wang, Lin] Xian Technol Univ, Xian Key Lab Act Photoelect Imaging Detect Technol, Xian 710021, Peoples R China

  Affiliations:Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; Xi'an Jiaotong University; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Xi'an Technological University

  Publication Year:2024

  Volume:63

  Issue:34

  Start Page:8890

  End Page:8897

  DOI Link:http://dx.doi.org/10.1364/AO.545170

  数据库ID（收录号）:WOS:001368007400004
• Record 14 of
  
  Title:Particle delivery in generalized optical vortex conveyor belts with a uniform orbital flow
  
  Author Full Names:Gao, Wenyu; Zhou, Yuan; Li, Xing; Zhang, Yanan; Zhang, Qiang; Li, Manman; Yu, Xianghua; Yan, Shaohui; Xu, Xiaohao; Yao, Baoli

  Source Title:PHOTONICS RESEARCH

  Language:English

  Document Type:Article

  Keywords Plus:PHASE

  Abstract:Perfect optical vortex (POV) beams offer a phase-gradient route to convey small particles along a tunable circular path or belt. The prevailing generalized POV method can be used to reshape the conveyor belt, but it usually deteriorates the orbital energy flow of field, leading to unstable conveying speed or even creating unwanted optical traps that prevent transportation. Here, we demonstrate optical conveyor belts with customized profiles and a uniform orbital flow over the whole transporting region by integrating isometric uniform sampling and random phases into the generalized POV generation algorithm. Smooth delivery of metallic particles, inaccessible to conventional generalized POV methods, is achieved at an almost even speed. We also demonstrate a dual-belt conveyor for delivering large metal microparticles, which experience repulsive intensity-gradient forces and thus are unable to be manipulated by a single belt. Our results present a unique addition to the toolbox of optical manipulation and would facilitate the development of small-scale drug delivery microsystems. (c) 2024 Chinese Laser Press

  Addresses:[Gao, Wenyu; Zhou, Yuan; Li, Xing; Zhang, Yanan; Zhang, Qiang; Li, Manman; Yu, Xianghua; Yan, Shaohui; Xu, Xiaohao; Yao, Baoli] Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China; [Gao, Wenyu; Zhou, Yuan; Li, Xing; Zhang, Yanan; Zhang, Qiang; Yao, Baoli] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

  Affiliations:Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; State Key Laboratory of Transient Optics & Photonics; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS

  Publication Year:2024

  Volume:12

  Issue:12

  Start Page:2881

  End Page:2890

  DOI Link:http://dx.doi.org/10.1364/PRJ.539718

  数据库ID（收录号）:WOS:001381806600015
• Record 15 of
  
  Title:Application of DS-DFT to the Fine Spectral Estimation of High-Noise Signals
  
  Author Full Names:Qin, Lin; Dang, Suihu; Fu, Di; Feng, Yutao

  Source Title:ELECTRONICS

  Language:English

  Document Type:Article

  Keywords Plus:FREQUENCY ESTIMATION; FILTER; MODEL

  Abstract:This paper presented an extended double-subsegment discrete Fourier transform (DS-DFT) algorithm as a tool for the fine spectral estimation of high-noise environments, which was previously effective in low-noise scenarios, and as such, its application to the analysis of noisy signals observed by a satellite-based interferometer was investigated. The observation of satellite-borne Doppler asymmetric spatial heterodyne spectroscopy (DASH) was first simulated to obtain the signals of low- and high-noise levels; then, a practical criterion to classify noise levels in the interferograms based on the DS-DFT results was introduced and validated by calculating the SNR. For high-noise signals, DS-DFT remains robust by employing phase differences and amplitude ratios for fine frequency estimation.

  Addresses:[Qin, Lin] Yangtze Normal Univ, Sch Elect Informat Engn, Chongqing 408100, Peoples R China; [Dang, Suihu] Yangtze Normal Univ, Key Lab Micro Nano Optoelect Devices & Intelligent, Chongqing 408100, Peoples R China; [Fu, Di; Feng, Yutao] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol, Xian 710049, Peoples R China

  Affiliations:Yangtze Normal University; Yangtze Normal University; Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS

  Publication Year:2024

  Volume:13

  Issue:24

  Article Number:5057

  DOI Link:http://dx.doi.org/10.3390/electronics13245057

  数据库ID（收录号）:WOS:001386843700001
• Record 16 of
  
  Title:Hierarchical existential prior based on expanded pseudo-label for crack detection
  
  Author Full Names:Wang, Nan; Fang, Jie; Yin, Jianfu; Cao, Xiaoqian

  Source Title:REVIEW OF SCIENTIFIC INSTRUMENTS

  Language:English

  Document Type:Article

  Keywords Plus:NETWORK

  Abstract:Road crack detection approaches based on the image processing technique have attracted much attention during the past decade due to their convenience and efficiency, but most of them cannot achieve the expected performances due to the complex background interference and severe category imbalance of road images. This paper presents a hierarchical existential prior based on an expanded pseudo-label for crack detection. In particular, the framework contains three variants of U-Net, and each sub-network is trained by pseudo-labels generated by transforming semantic categories of non-crack pixels distributed in the neighborhoods of crack ones. Notably, the expansion degrees of labels for three sub-networks are set in hierarchical descending order. In other words, the crack samples of pseudo-labels for the latter sub-network are a subset of pseudo-labels for the former one, and we define it as an existential prior, which can optimize the network in a coarse-to-fine fashion and refine the detection result gradually. In addition, we utilize a hybrid loss consisting of IoU, SSIM, and focal loss to optimize the network in different aspects, including image-aspect, patch-aspect, and pixel aspect in the training phase, which can improve the structural representation capability of the model. In addition, we present a dynamic hyper-parameter adjustment strategy to balance the weight coefficients of different loss terms, which can enhance the robustness of the model for various practical scenes. Finally, the proposed method achieves 11.36%, 29.76%, and 26.73% in terms of F beta on CrackTree200, Crack Forest, and ALE datasets, respectively, which sufficiently demonstrate its effectiveness and superiority.

  Addresses:[Wang, Nan] Hainan Normal Univ, Sch Informat Sci & Technol, Haikou 571158, Peoples R China; [Fang, Jie] Xian Univ Posts & Telecommun, Sch Telecommun & Informat Engn, Xian 710121, Shaanxi, Peoples R China; [Yin, Jianfu] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol, Xian 710119, Shaanxi, Peoples R China; [Cao, Xiaoqian] Shaanxi Univ Sci & Technol, Sch Elect & Control Engn, Xian 710021, Shaanxi, Peoples R China

  Affiliations:Hainan Normal University; Xi'an University of Posts & Telecommunications; Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; Shaanxi University of Science & Technology

  Publication Year:2024

  Volume:95

  Issue:12

  Article Number:123706

  DOI Link:http://dx.doi.org/10.1063/5.0217515

  数据库ID（收录号）:WOS:001385888600004
• Record 17 of
  
  Title:Non-Cooperative Target Ranging Based on High-Orbit Single-Star Temporal-Spatial Characteristics
  
  Author Full Names:Zhang, Derui; Wang, Hao; Zhao, Qing

  Source Title:APPLIED SCIENCES-BASEL

  Language:English

  Document Type:Article

  Abstract:A visible light camera payload with star-sensitive functionality was installed to measure the distance between a non-cooperative target satellite and a high-orbit satellite. The rotation matrix was used to calculate the pointing vector from the center of the satellite's star-sensitive camera axis to the target satellite. Multiple position imaging was achieved, and the moving window approach was used to establish two sets of equations relating the pointing vectors to the positions of binary satellites. To simplify the calculations, the target satellite's eccentricity was assumed to be small (0 to 0.001), allowing elliptical orbits to be approximated as circular. Additionally, short-interval (1-min) imaging measurements were taken, assuming a small inclination of the target satellite (0.0 degrees to 0.4 degrees). This resulted in the construction of a ranging model with high accuracy, producing a ranging error of less than 5% of the actual distance.

  Addresses:[Zhang, Derui; Wang, Hao; Zhao, Qing] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China; [Zhang, Derui] Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian 710049, Peoples R China; [Zhang, Derui] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

  Affiliations:Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; Xi'an Jiaotong University; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS

  Publication Year:2024

  Volume:14

  Issue:23

  Article Number:11232

  DOI Link:http://dx.doi.org/10.3390/app142311232

  数据库ID（收录号）:WOS:001376226700001
• Record 18 of
  
  Title:Controllable dual-layer twisted array source
  
  Author Full Names:Zhang, Shaohua; Zhou, Zhenglan; Zhou, Yuan; Qu, Jun

  Source Title:OPTICS LETTERS

  Language:English

  Document Type:Article

  Keywords Plus:ORBITAL ANGULAR-MOMENTUM; PROPAGATION

  Abstract:The use of array structures in optical communication and trapping significantly enhances information capacity and trapping efficiency, while twisted beams present promising applications in both fields. However, it remains a considerable technical challenge to control and stabilize large-scale twisted beam arrays while ensuring both beam stability and multi-structural integrity. In this study, we constructed a twisted array of Schell-model sources and introduced an array twist parameter to characterize the global rotational characteristics of these randomly fluctuating optical fields. The results show that optimizing parameter settings allows for effective control of the rotational structure of beam arrays, enabling reverse rotation of the dual-layer beam structure. Additionally, the stability of the twisted array structure is effectively maintained through the dual- layer twist characteristics. Precise control of the dual-layer twisted beams enables the creation of complex optical field structures, thereby enhancing the flexibility of optical manipulation and further improving the trapping efficiency of particles and the bandwidth of optical communication. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

  Addresses:[Zhang, Shaohua; Qu, Jun] Anhui Normal Univ, Anhui Prov Key Lab Control & Applicat Optoelect In, Wuhu 241000, Anhui, Peoples R China; [Zhou, Zhenglan] Huainan Normal Univ, Sch Elect Engn, Huainan 232038, Peoples R China; [Zhou, Yuan] Chinese Acad Sci, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China

  Affiliations:Anhui Normal University; Huainan Normal University; Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; State Key Laboratory of Transient Optics & Photonics

  Publication Year:2024

  Volume:49

  Issue:23

  Start Page:6657

  End Page:6660

  DOI Link:http://dx.doi.org/10.1364/OL.543750

  数据库ID（收录号）:WOS:001380259600008
• Record 19 of
  
  Title:Innovative multi-class segmentation for brain tumor MRI using noise diffusion probability models and enhancing tumor boundary recognition
  
  Author Full Names:Liu, Zengxin; Ma, Caiwen; She, Wenji; Xie, Meilin

  Source Title:SCIENTIFIC REPORTS

  Language:English

  Document Type:Article

  Abstract:Medical imaging, notably Magnetic Resonance Imaging (MRI), plays a vital role in contemporary healthcare by offering detailed insights into internal structures. Addressing the escalating demand for precise diagnostics, this research focuses on the challenges of multi-class segmentation in MRI. The proposed algorithm integrates diffusion models, capitalizing on their efficacy in capturing microstructural details, emphasizing the intricacies of human anatomy and tissue variations that challenge segmentation algorithms. Introducing the Diffusion Model, previously successful in various applications, the research applies it to medical image analysis. The method employs a two-step approach: a diffusion-based segmentation model and a dedicated network for enhancing tumor (ET) boundary recognition. Training is guided by a combined loss function, emphasizing Weighted Cross-Entropy and Weighted Dice Loss. Experiments, conducted using the BraTS2020 dataset for brain tumor segmentation, showcase the proposed algorithm's competitive results, particularly in enhancing accuracy for the challenging ET region. Comparative analyses underscore its superiority over existing methods, emphasizing efficiency and simplicity in clinical implementation. In conclusion, this research pioneers an innovative approach that combines diffusion models and ET boundary recognition to optimize multi-class segmentation for brain tumors. The method holds promise for improving clinical diagnosis and treatment planning, providing accurate and interpretable segmentation results without the need for high-end equipment.

  Addresses:[Liu, Zengxin; Ma, Caiwen; She, Wenji; Xie, Meilin] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China; [Liu, Zengxin] Univ Chinese Acad Sci, Sch Optoelect, Beijing 101408, Peoples R China

  Affiliations:Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS

  Publication Year:2024

  Volume:14

  Issue:1

  Article Number:29576

  DOI Link:http://dx.doi.org/10.1038/s41598-024-78688-6

  数据库ID（收录号）:WOS:001367580400032
• Record 20 of
  
  Title:Efficient anti-icing/deicing via photothermal-wind synergistic effects on femtosecond laser-induced superhydrophobic graphene
  
  Author Full Names:Song, Xinghao; Yin, Kai; Li, Xun; Wang, Lingxiao; Yang, Pengyu; Pei, Jiaqing; Huang, Yin; Arnusch, Christopher J.; Li, Guoqiang

  Source Title:JOURNAL OF MATERIALS CHEMISTRY A

  Language:English

  Document Type:Article

  Abstract:Photothermal superhydrophobic surfaces have been demonstrated for anti-icing/deicing applications. However, preparing these materials using simple and environmentally friendly methods remains a challenge. Herein, a high-efficiency energy utilization strategy based on a photothermal-wind synergistic effect combined with superhydrophobicity has been proposed for anti-icing/deicing. Using one-step femtosecond laser direct writing technology, we modified a polyether ether ketone surface, which resulted in a superhydrophobic surface with photothermal effects. The optimized fabrication condition was laser treatment with velocity of 80 mm s-1 (LT-V80), which gave a surface possessing a high water contact angle (similar to 160.9 degrees) and a low rolling angle (similar to 3 degrees), and excellent self-cleaning properties were seen. Furthermore, LT-V80 showed high light absorptivity (similar to 94.6%), which caused the surface temperature to increase by 44.5 degrees C under 1.0 sun illumination. The addition of wind to the system resulted in a synergistic effect together with the photothermal and superhydrophobic properties, and caused a 87.1% reduction of the deicing time and a 220.3% increase in the icing time. This strategy also demonstrated good deicing efficiency in a cold outdoor environment. An efficient solar energy utilization strategy as demonstrated by LT-V80 indicates that efficient anti-icing/deicing is possible using simple, environmentally friendly, and low cost fabrication methods.

  Addresses:[Song, Xinghao; Yin, Kai; Wang, Lingxiao; Yang, Pengyu; Pei, Jiaqing; Huang, Yin] Cent South Univ, Sch Phys, Hunan Key Lab Nanophoton & Devices, Changsha 410083, Peoples R China; [Yin, Kai] Cent South Univ, Coll Mech & Elect Engn, State Key Lab High Performance & Complex Mfg, Changsha 410083, Peoples R China; [Yin, Kai] Huazhong Univ Sci & Technol, State Key Lab Intelligent Mfg Equipment & Technol, Wuhan 430000, Peoples R China; [Li, Xun] Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Xian 710119, Peoples R China; [Arnusch, Christopher J.] Ben Gurion Univ Negev, Zuckerberg Inst Water Res, Jacob Blaustein Inst Desert Res, Dept Desalinat & Water Treatment, Sede Boqer Campus, IL-8499000 Midreshet Ben Gurion, Israel; [Li, Guoqiang] Southwest Univ Sci & Technol, Sch Manufacture Sci & Engn, Key Lab Testing Technol Mfg Proc, Minist Educ, Mianyang 621010, Peoples R China

  Affiliations:Central South University; Central South University; Huazhong University of Science & Technology; Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; State Key Laboratory of Transient Optics & Photonics; Ben Gurion University; Southwest University of Science & Technology - China

  Publication Year:2024

  Volume:13

  Issue:1

  Start Page:205

  End Page:213

  DOI Link:http://dx.doi.org/10.1039/d4ta06520d

  数据库ID（收录号）:WOS:001367701300001
• Record 21 of
  
  Title:Static and structural dynamic analysis of thick panel kirigami deployable structures
  
  Author Full Names:Li, Junlan; Wang, Cheng; Yan, Yucheng; Wang, Peng; Zhao, Jieliang; Zhang, Dawei

  Source Title:AEROSPACE SCIENCE AND TECHNOLOGY

  Language:English

  Document Type:Article

  Keywords Plus:ORIGAMI; DESIGN

  Abstract:Thick panel origami and kirigami concepts have been wildly used to design novel deployable structures in various engineering applications. However, these novel folding methods usually involve complex connected topologies, which may lead to unclear and intricate characterized relationships between system properties and structural parameters, e.g., the position of cutting creases, design parameters and hinge stiffness arrangement, etc. In this paper, we propose theoretical models to describe the static and dynamic properties of thick panel kirigami structure in the fully deployed configuration. Firstly, the connected topology of the origami and kirigami structure is analysed, and the internal coupling topology of the structure is obtained. Based on the compliant matrix method, the static model of the structure is presented, and the different crease cutting modes of origami and kirigami arrays are discussed. Then, the motion modes of slight oscillation of structure are discussed and the structural dynamic model is obtained based on the Lagrange equation and validated by simulation. On this basis, the sensitivity analysis of the parameters is carried out, and the optimization model is given based on the comprehensive performance evaluation function. A physical prototype is optimized and tested, which indicates that our model is valid. This paper provides models for the structural static and dynamic properties of thick panel kirigami structures with complex connected topology, and the findings have a potential to be developed in other thick panel structures with origami and kirigami folding concepts.

  Addresses:[Li, Junlan; Yan, Yucheng; Wang, Peng; Zhang, Dawei] Tianjin Univ, Key Lab Mech & Equipment Design, Minist Educ, Tianjin 300072, Peoples R China; [Li, Junlan; Yan, Yucheng; Wang, Peng; Zhang, Dawei] Tianjin Univ, Sch Mech Engn, Tianjin 300072, Peoples R China; [Wang, Cheng] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China; [Zhao, Jieliang] Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China

  Affiliations:Tianjin University; Tianjin University; Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; Beijing Institute of Technology

  Publication Year:2024

  Volume:155

  Article Number:109753

  DOI Link:http://dx.doi.org/10.1016/j.ast.2024.109753

  数据库ID（收录号）:WOS:001366543300001
• Record 22 of
  
  Title:Virtual restoration of ancient tomb murals based on hyperspectral imaging
  
  Author Full Names:Zeng, Zimu; Qiu, Shi; Zhang, Pengchang; Tang, Xingjia; Li, Siyuan; Liu, Xuebin; Hu, Bingliang

  Source Title:HERITAGE SCIENCE

  Language:English

  Document Type:Article

  Keywords Plus:FUSION

  Abstract:The virtual restoration of historic murals holds immense importance in the realm of cultural heritage preservation. Currently, there are three primary technical issues. First and foremost, it is imperative to delineate the precise location where the mural necessitates restoration. Second, the original color of the mural has changed over time, resulting in a difference from its current appearance. Then, while the method utilizing convolutional neural networks is effective in restoring small defaced areas of murals, its effectiveness significantly diminishes when applied to larger areas. The primary objectives of this paper are as follows: (1) To determine the large and small areas to be restored, the authors employ hyperspectral super-pixel segmentation and support vector machine-Markov random field (SVM-MRF) classification. (2) The authors transform the hyperspectral mural images into more realistic and accurate red-green-blue (RGB) images using the Commission Internationale de l'Eclairage (CIE) standard colorimetric system. (3) The authors restored the images respectively using convolutional neural network and matching image block-based approaches depending on the size of the areas to be mended. The proposed method has enhanced the image quality assessment (IQA) in terms of both color quality and restoration effects. In contrast to the pseudo-color fusion method, the color optimization algorithm described in this research enhances the multi-scale image quality (MUSIQ) by 8.42%. The suggested technique enhances MUSIQ by 2.41% when compared to the convolutional neural network-based image inpainting algorithm.

  Addresses:[Zeng, Zimu; Qiu, Shi; Zhang, Pengchang; Li, Siyuan; Liu, Xuebin; Hu, Bingliang] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol, Xian 710119, Peoples R China; [Zeng, Zimu] Univ Chinese Acad Sci, Sch Optoelect, Beijing 101408, Peoples R China; [Tang, Xingjia] Northwest Polytech Univ, Inst Culture & Heritage, Xian 710072, Peoples R China

  Affiliations:Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Northwestern Polytechnical University

  Publication Year:2024

  Volume:12

  Issue:1

  Article Number:410

  DOI Link:http://dx.doi.org/10.1186/s40494-024-01501-0

  数据库ID（收录号）:WOS:001360438800002
• Record 23 of
  
  Title:Adaptive range gating based on variational Bayesian inference for space debris ranging with spaceborne single-photon LiDAR
  
  Author Full Names:Tian, Yuan; Hu, Xiaodong; Zhao, Yixin; Zhang, Xuan; Wang, Dingjie; Chen, Songmao; Hao, Wei; Xie, Meilin; Su, Xiuqin

  Source Title:OPTICS LETTERS

  Language:English

  Document Type:Article

  Abstract:To enhance the accuracy of space debris localization, space- borne single-photon LiDAR (SSPL) presents a promising technique for accurate target ranging. Extended Kalman filtering (EKF) plays a crucial role in range gating under high dynamic and nonlinear motion conditions of space debris, ensuring accurate state estimation and prior distance data. However, unknown and time-varying statistics of process and measurement noise significantly degrade state estimation accuracy, posing risks of filter divergence and reduced photon reception, ultimately rendering range gating ineffective. To address this challenge, we propose an adaptive range gating method based on variational Bayesian adaptive extended Kalman filtering (ARG-VBAEKF). This method leverages variational Bayesian (VB) posterior approximation to estimate the joint distribution of state and noise. Simulation results demonstrate that ARG-VBAEKF achieves accurate state and noise estimation, thereby effectively enhancing range gating performance in SSPL-based space debris ranging. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

  Addresses:[Tian, Yuan; Zhao, Yixin; Zhang, Xuan; Wang, Dingjie; Chen, Songmao; Hao, Wei; Xie, Meilin; Su, Xiuqin] Xian Inst Opt & Precis Mech, Chinese Acad Sci, Key Lab Space Precis Measurement Technol, Xian 710119, Peoples R China; [Tian, Yuan; Hu, Xiaodong; Zhao, Yixin; Zhang, Xuan; Wang, Dingjie; Chen, Songmao; Hao, Wei; Xie, Meilin; Su, Xiuqin] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China; [Tian, Yuan; Zhao, Yixin; Zhang, Xuan; Wang, Dingjie] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Tian, Yuan; Zhao, Yixin; Zhang, Xuan; Wang, Dingjie; Chen, Songmao; Hao, Wei; Xie, Meilin; Su, Xiuqin] Pilot Natl Lab Marine Sci & Technol, Qingdao 266237, Peoples R China

  Affiliations:Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Laoshan Laboratory

  Publication Year:2024

  Volume:49

  Issue:22

  Start Page:6561

  End Page:6564

  DOI Link:http://dx.doi.org/10.1364/OL.533546

  数据库ID（收录号）:WOS:001379609100006
• Record 24 of
  
  Title:Advanced data augmentation techniques coupled with enhanced particle swarm optimization for predicting total phosphorus concentrations in limited transmission spectra samples: A case study on the Yangtze River
  
  Author Full Names:Zhang, Guohao; Wang, Cailing; Wang, Hongwei; Yu, Tao

  Source Title:JOURNAL OF WATER PROCESS ENGINEERING

  Language:English

  Document Type:Article

  Keywords Plus:ALGORITHM

  Abstract:Accurate prediction of total phosphorus concentration in water bodies is crucial for effective water pollution control and management. However, obtaining real-world water samples presents challenges such as being costly, time-consuming, or difficult. To boost prediction accuracy, this study introduces novel methodologies integrating advanced data augmentation techniques with enhanced optimization algorithms. In the data augmentation techniques, we employ a novel Oversampling Nearest Neighbor Generative Adversarial Network (ONNGAN) to augment the collected sample data, thereby mitigating issues arising from poor model training due to insufficient sample numbers. Regarding the enhanced particle swarm optimization, we introduce the Ant Colony Cooperative Particle Swarm Optimization (ACCPSO) algorithm, which enhances traditional particle swarm optimization by incorporating several strategic improvements. These enhancements reduce the likelihood of the algorithm getting stuck in local optima and accelerate its convergence speed. The ACCPSO algorithm is employed to automatically optimize the hyperparameter combinations for a Convolutional Neural Network (CNN), and the optimized CNN is then used to predict total phosphorus concentrations in water bodies. By combining these two advanced algorithms, we can more effectively explore the complex nonlinear relationships in transmission spectrum data, thereby enhancing prediction accuracy. The experimental results indicate that, following data augmentation, the ACCPSO-CNN model achieves an R2 of 0.9773, an RMSE of 0.0018, and an MAE of 0.0005, outperforming other benchmark models such as Support Vector Regression and Partial Least Squares Regression across all evaluation metrics. In summary, our research provides a powerful and practical tool for water quality monitoring and pollution control, offering broad application prospects.

  Addresses:[Zhang, Guohao; Wang, Cailing] Xian Shiyou Univ, Coll Comp Sci, Xian 710065, Peoples R China; [Wang, Hongwei] Northwestern Polytech Univ, Sch Artificial Intelligence Opt & Elect, Xian 710065, Peoples R China; [Yu, Tao] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710065, Peoples R China

  Affiliations:Xi'an Shiyou University; Northwestern Polytechnical University; Chinese Academy of Sciences; Xi'an Institute of Optics & Precision Mechanics, CAS

  Publication Year:2024

  Volume:68

  Article Number:106547

  DOI Link:http://dx.doi.org/10.1016/j.jwpe.2024.106547

  数据库ID（收录号）:WOS:001358824800001