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Underwater arbitrary ranging based on chirped pulse interferometry with a mode-locked laser

Journal of Lightwave technology 2025年第11期43卷 5235-5243页

作者： Shi, Haonan Zhao, Haihan Xu, Xinyang Zhu, Zhiwei Zhai, Jingsheng Li, Xiaobo Tianjin University School of Marine Science and Technology Tianjin300072 China Research Institute of China Electronics Technology Group Corporation Science and Technology on Electro-Optical Information Security Control Laboratory No. 53 Tianjin300308 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong999077 Hong Kong Nanjing University of Aeronautics and Astronautics Key Laboratory of Space Photoelectric Detection and Perception Ministry of Industry and Information Technology Nanjing211106 China

Underwater distance measurement and length sensing, as fundamental functions of geoscience, are integrated into underwater robots and vessels in various forms of sensor payloads and play a crucial role in a wide range of remote sensing applications. Advanced laser-based detection systems and algorithms are essential for underwater tasks, such as detecting damage in underwater pipelines and conducting detailed structural health assessments. In this paper, we experimentally demonstrated an arbitrary underwater ranging system by the chirped pulse interferometry with a mode-locked laser. Water's inherent characteristic introduces dispersion, enabling unique distance discrimination. Adjusting the repetition frequency allows us to acquire the interference spectrum. A long fiber delay line, stabilized by the servo-controlled system, eliminates the ranging dead zone. The widest fringe of the interference spectrum, corresponding to an instantaneous repetition frequency, indicates the arbitrary measured distance. Leveraging a charge-coupled device detection module, we achieved an update rate of 13.5 Hz for the interference spectrum. Experimental results show a precise distance difference within 59.8 μm at the 5 m range underwater without the dead zone. © 2025 IEEE. All rights reserved.

关键词： Laser mode locking

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Study on the Medium Fusion Data Storage technology for High Performance Airborne Sensors 3

Study on the Medium Fusion Data Storage Technology for High ...

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3rd IEEE International Conference on Intelligent technology and Embedded Systems, ICITES 2023

作者： Xie, Dan Tian, Haishan Sun, Yuxin Zhang, Mingru Huang, Yawei Tang, Chang School of Physics and Electronics Hunan Normal University Changsha China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjing China

ISBN: (纸本)9798350343755

The data rate of high-performance airborne sensors is much higher than the wireless data transfer rate in many detection applications, so the onboard data storage systems are usually used to store the sensor data. There is a problem in the onboard data storage that the frequency of address jumps among incontinuous areas is very high due to the high data updating frequency of the FAT (File Allocation Table) and FDT (File Directory Table), which would significantly reduce the data storage speed. This is because the most widely used NAND (Not And) flash has a long response time when storing the data in the incontinuous areas. In order to solve the problem, a called medium fusion storage method, which uses multiple mediums time sharing to store the data of file areas and data region, is proposed in this study. The performance of the proposed method is tested on an actual data storage system of the airborne sensor. The experimental results show that medium fusion storage method significantly reduces the data updating frequency of the FAT and FDT in the data storage, and the response time is negligible compared with the actual data writing time. © 2023 IEEE.

关键词： Data transfer

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Design and Implementation of High-Speed Serial Transmission for ADC Based on JESD204B 3

Design and Implementation of High-Speed Serial Transmission ...

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3rd IEEE International Conference on Intelligent technology and Embedded Systems, ICITES 2023

作者： Huang, Yawei Tian, Haishan Zhang, Mingru Sun, Yuxin Xie, Dan Tang, Chang School of Physics and Electronics Hunan Normal University Changsha China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjing China

ISBN: (纸本)9798350343755

Currently, as the resolution of sensors such as radar continues to improve, the signal bandwidth is rapidly increasing. There is a growing demand for higher sampling rates and data transmission rates in Analog-to-Digital Converters (ADCs). However, the parallel transmission commonly used in ADCs faces issues such as high crosstalk and difficulties in transmission synchronization. In response to this problem, this paper proposes a method for the design and implementation of a high-speed serial data transmission interface based on JESD204B. Specifically, it utilizes Xilinx's ZYNQ-7 series FPGA and ADC as the core components and presents clock synchronization design, ADC circuit design, and FPGA 204B IP design methods. Experimental testing was conducted using selected link parameters (LMFS=4222) as an example. The experimental results demonstrate that correct JESD204B interface data transmission for four channels was achieved at a data rate of 10 Gbps, thus validating the feasibility of the proposed high-speed transmission link design based on JESD204B in this paper. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Design Compact YOLO based Network for Small Target Detection on Infrared Image

Design Compact YOLO based Network for Small Target Detection...

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2022 Chinese Automation Congress, CAC 2022

作者： Liu, Shuang Liu, Zhicheng Li, Yuhai Liu, Wancheng Ge, Chenyang Liu, Longjun Xi'an China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin China

ISBN: (纸本)9781665465335

most YOLO object detection neural networks prefer to focus on traditional RGB image, but previous studies rarely consider special YOLO network with compact architecture for infrared image. In this paper, we analyze original YOLO network architecture, and we propose a compact YOLO based network by using different blocks from previous work for small target detection on infrared image. We use small target detection layer, GhostConv convolution, Focus structure, Focal EIOU Loss and soft NMS modules to improve original YOLO network structure, which improves the accuracy and speed of target detection for infrared image. The experimental results show that the accuracy of target detection of original model can be effectively improved by adding the small target detection layer, the Focus structure and the BI-FPN structure. By replacing the GhostConv convolution, the calculation speed is significantly improved. At last, after the model is quantized and deployed with NCNN framework, the object detection speed can reached to 35ms per infrared image. © 2022 IEEE.

关键词： Object detection

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Design an Efficient DNN Inference Framework with PS-PL Synergies in FPGA for Edge Computing

Design an Efficient DNN Inference Framework with PS-PL Syner...

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2022 Chinese Automation Congress, CAC 2022

作者： Liu, Wancheng Li, Yuhai Yang, Yining Zhu, Jinyu Liu, Longjun Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin China Xi'an China

ISBN: (纸本)9781665465335

in recent years, Deep Neural Network (DNN) based methods have achieved great success for changing inflexible machine to intelligent and live system. Internet of Things (IoT) applications equipped with DNN in domains such as self-driving, speech processing and video surveillance particular challenges. Since DNNs are memory-/computing- intensive applications, FPGAs are customized to accelerate DNN on edge system due to their low latency and high energy efficiency. However, embedded CPU is usually essential for IoT system and single accelerator of FPGA is hard to gain maximized performance of the whole IoT system. Therefore, we design an efficient DNN inference framework with programming system (PS, e.g., ARM CPU) and programming logic (PL, e.g. FPGA) synergies for intelligent IoT system. Compared with the common IoT system only separately leverages FPGA for DNN accelerating and ARM for other tasks, our framework can make ARM and FPGA jointly accelerate DNN inference from the beginning. Our PS-PL co-design approach can take full advantage of the merits of ARM (control operations) and FPGA (parallel computing operations) for various DNN model accelerating. We implemented our co-design framework on Zynq SoCs. The experimental results show that our framework can achieve maximal 205.9 GOPs/s DNN inference accelerating under 6.2W while it would not affect other CPU tasks running on IoT system. © 2022 IEEE.

关键词： Internet of things

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Pointing error modeling and analysis of an electro-optical reconnaissance system

Pointing error modeling and analysis of an electro-optical r...

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2022 Applied Optics and Photonics China: Infrared Devices and Infrared technology;and Terahertz technology and Applications, AOPC 2022

作者： Chen, Hai-Xia Gao, Wen-Qing China Electronics Technology Group Corp. Science and Technology on Electro-Optical Information Security Control Laboratory Airport Economic Zone Tianjin300308 China

ISBN: (纸本)9781510662247

In the process of guiding the target device, the pointing and guidance accuracy of the on-board electro-optical reconnaissance system is affected by the relative installation position of the equipment, as it can not realize the coaxial installation with the guided device. According to the structural characteristics of the equipment, the mathematical model of target orientation function from the image plane coordinate system of the electro-optical reconnaissance system to the equipment base coordinate system is constructed, the error sources affecting the target pointing accuracy are analyzed, and the target pointing error model is established. The Monte Carlo method is used to analyze the relationship between the pointing error and its error sources. The probability density distribution of each error source is established. The target pointing accuracy performance under the influence of different errors is analyzed. And the sensitive factors affecting the pointing accuracy are figured out, which provides a certain theoretical guidance for the error allocation in the accuracy design stage. © 2023 SPIE.

关键词： Monte Carlo methods

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Non-stationary Interference Mitigation for GNSS Using Sparse Representation

Non-stationary Interference Mitigation for GNSS Using Spars...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Ren, Yuetao Zhi, Yongfeng Gao, Huan Zhang, Jun School of Automation Northwestern Polytechnical University Xi’an710072 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300308 China

ISBN: (纸本)9789811966125

electromagnetic interference poses a threat to global navigation satellite systems (GNSS) used in various civilian applications. Sparse representation has been extensively studied for interference cancellation. However, dictionaries of non-stationary signals are difficult to construct due to their time-varying characteristic. Therefore, the mitigation of non-stationary interference is still a challenging issue. This paper proposes an adaptive dictionary construction approach for sparse representation of non-stationary interference. The proposed algorithm utilizes the non-stationary signal analysis tool, Wigner-Ville distribution (WVD), to provide prior knowledge. The overcomplete dictionary is constructed adaptively based on the instantaneous frequencies estimated from WVD. The proposed approach can reconstruct non-stationary interference successfully exploiting the adaptive dictionary. The simulation results confirm that the proposed interference suppression algorithm can successfully mitigate the interference and achieve GNSS signal acquisitions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wigner-Ville distribution

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6G Network Traffic Intrusion Detection Using Multiresolution Auto-encoder and Feature Matching Discriminator 5th

6G Network Traffic Intrusion Detection Using Multiresolution...

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5th EAI International Conference on 6G for Future Wireless Networks, 6GN 2022

作者： Li, Yuhai Sun, Yuxin He, Dong Xi, Liang Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300300 China School of Computer Science and Technology Harbin University of Science and Technology Harbin150080 China

ISBN: (纸本)9783031360107

With the development of 6G technology, security and privacy have become extremely important in the face of larger network traffic bandwidth. An effective intrusion detection system can deal with the network attacks. Deep learning has been developed in the field of intrusion detection, which can identify normal and abnormal traffic. However, existing methods cannot guarantee good performance in accuracy and efficiency. In this paper, based on the autoencoder and generative adversarial network, the multiresolution autoencoder is adopted in the network traffic feature extraction, which can obtain different encoding lengths and guarantee better data reconstruction. In addition, we add an extra feature matching loss to encourage the discriminator to get more discriminative information from the reconstructed samples. Our experimental results on the CIC-IDS2018 dataset indicates that compared with autoencoder and generative adversarial network, our model can effectively improve the detection accuracy and can be applied to 6G network traffic security detection. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Intrusion detection

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Classification of Deforestation Factors in 6G Satellite Forest Images 5th

Classification of Deforestation Factors in 6G Satellite Fore...

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5th EAI International Conference on 6G for Future Wireless Networks, 6GN 2022

作者： Li, Yuhai Sun, Yuxin Meng, Xianglong Xi, Liang Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300300 China School of Computer Science and Technology Harbin University of Science and Technology Harbin150080 China

ISBN: (纸本)9783031360107

The terrestrial satellite network will play an essential role in 6G. Through the satellite system, people can obtain a lot of ground image information to process tasks and feedback. Forest resource is an essential resource. Determining the causes of deforestation is crucial for the development and implementation of forest protection plans. In this article, we propose a novel deep neural network model for distinguishing drivers of deforestation events from satellite forest images. To solve the problems of image rotation caused by satellite angle rotation and image blurring caused by extreme weather occlusion during satellite image acquisition, we add data enhancement and a self-supervised rotation loss to the model to improve the robustness and adaptability. We use deforestation maps generated from Landsat 8 satellite imagery as a dataset and demonstrate that our approach achieves better results than the baselines. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Deforestation

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electro-optically Q-switching performance of diode-pumped HoGdVO4 laser

Electro-optically Q-switching performance of diode-pumped Ho...

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2022 Conference on Infrared, Millimeter, Terahertz Waves and Applications, IMT 2022

作者： Wu, Jiaze Duan, Xiaoming Ding, Yu Ju, Youlun School of Astronautics Harbin Institute of Technology Harbin150001 China National Key Laboratory of Tunable Laser Technology Harbin Institute of Technology Harbin150001 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300308 China

ISBN: (纸本)9781510662476

We proposed a Ho:GdVO4 laser operating at 2.05 µm which was directly in-band dual-end-pumped by a pair of 1.94 μm fiber-coupled laser diodes (LD). A Ho:GdVO4 crystal with doping of 1.0 at.% was used as the gain medium. In continuous-wave (CW) mode, we obtained the maximum output power of 6.5 W at 2047.9 nm with the absorbed pump power of 28 W, corresponding to a slope efficiency of 37.6 %. By using an LGS crystal as the electro-optical Q-switch, the highest peak power of 773.8 kW was obtained at a pulse repetition frequency (PRF) of 1 kHz, corresponding to a maximum pulse energy of 3.25 mJ and a pulse width of 4.2ns. © 2023 SPIE.

关键词： Q switching

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