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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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Artificial Intelligence-Aid OTFS Receiver: Design and Performance Evaluation

Artificial Intelligence-Aid OTFS Receiver: Design and Perfor...

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2023 International Conference on Ubiquitous Communication, Ucom 2023

作者： Wang, Chenxi Qian, Li Ping Zhu, Huijie College of Information Engineering Zhejiang University of Technology Hangzhou China The 36th Research Institute of China Electronics Technology Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9798350340433

OTFS technology is attracting much attention due to its strong adaptability to high-speed mobility and high spectrum efficiency. Studies show that applying deep learning (DL) to traditional communication systems significantly improves their performance. To this end, this paper proposes an AI-Aid OTFS receiver to enhance the performance of OTFS systems in high-speed mobile communication scenarios. The proposed receiver employs two networks-a channel estimation network called TFNet and a decoding network called RecovNet. In the channel estimation module, TFNet performs more accurate channel estimation based on the results of traditional channel estimation methods. In the decoding module, RecovNet decodes the signal based on the equalized signals. To validate the superiority of our proposed receiver, we conduct comparative testing with a traditional receiver under the integer Doppler channel. The experimental results demonstrate that integrating DL technology in OTFS systems effectively enhances their performance. © 2023 IEEE.

关键词： Decoding

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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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Target-Before-Detect Algorithm for Passive MIMO Radar Based on Improved Particle Filter

Target-Before-Detect Algorithm for Passive MIMO Radar Based ...

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2022 Global Conference on Robotics, Artificial Intelligence and information technology, GCRAIT 2022

作者： Zhou, Yawen Zhu, Jiawei Song, Tingsong Yao, Siyi Lai, Rui Guo, Yuning School of Electronic Science and Technology University Chengdu China Information Security Control Laboratory Science and Technology on Communication Jiaxing China

ISBN: (数字)9781665481922

ISBN: (纸本)9781665481922

In order to improve the target detection performance of passive multiple-input-multiple-output (PMR) radar system, a Target-Before-Detect (TBD) algorithm based on improved particle filter is proposed in this paper. As a classical TBD algorithm, particle filter algorithm can realize the gain accumulation of target signal in time domain and effectively improve the performance of target detection. Although this algorithm has performed well in passive single-input-single-output (SISO) radar (PSR) systems, it cannot be directly applied to PMR systems. Therefore, an improved particle filtering algorithm based on passive MIMO radar is proposed in this paper. This method takes advantage of the PMR spatial accumulation and proposes a novel particle weight calculation method, which uses the false alarm probability distribution of detector to calculate the weight of the particle, so as to obtain the gain accumulation of the target in time and space. The simulation results show that the detection probability of the proposed algorithm can reach 90% even when the target-path signal-To-noise ratio (SNR) is low. Meanwhile, the good detection performance of the proposed algorithm is verified by comparing with the single frame detection results. © 2022 IEEE.

关键词： Probability distributions

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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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Simulation research on holographic modal wavefront sensing of atmospheric propagating laser 8

Simulation research on holographic modal wavefront sensing o...

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8th Symposium on Novel Photoelectronic Detection technology and Applications

作者： Li, Yuqing Cheng, Jingxin Yang, Haibo Ma, Wenchao Gu, Jianda Liu, Tongyu Science and Technology on Electro-Optical Information Security Control National Key Laboratory Tianjin300308 China

ISBN: (数字)9781510653122

ISBN: (纸本)9781510653115

The disturbance of atmospheric turbulence during laser transmission is a major problem in the field of high-energy laser transmission and communication. Fast and real time wavefront sensing is one of the key technologies in adaptive optical systems. For laser emission or communication systems with relatively smaller optical apertures and transmission distances, atmospheric aberration is mainly composed of low-order Zernike modes with weak intensity. Traditional Hartmann wavefront sensor works by regional segmentation and reconstruction of the wavefront plane, which need complicated matrix calculation, inducing considerable time delay. Its application in laser wavefront sensing can be technically sophisticated and redundant. Holographic modal wavefront sensing technology takes advantage of parallel modal detection method to obtain the intensity of specific modes of aberrations carried by the laser directly. With benefits of higher speed, smaller time delay, and compact system structure, it may be more suitable for atmospheric laser wavefront sensing. Here, we carried out simulation research on holographic modal wavefront sensor and its application in atmospheric laser wavefront sensing, the measuring accuracy and validation frontier of this technology are analyzed. The result provided informative support on high speed laser aberration sensing and correction. © 2022 SPIE

关键词： Atmospheric turbulence

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Minimum dispersion beamforming using modified conjugate gradient method

Minimum dispersion beamforming using modified conjugate grad...

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2021 International Conference on Electronic information Engineering and Computer Communication, EIECC 2021

作者： Song, Jinyang Wang, Wei Chen, Yan Science and Technology on Communication Information Security Control Laboratory China Cetc 36 Zhejiang Jiaxing China

ISBN: (数字)9781510653207

ISBN: (纸本)9781510653191

In order to solve linear constraint minimize dispersion problem in beamforming with non-Gaussian signals or noise, this paper proposed a real time adaptive beamforming technique based on modified conjugate gradient (MCG) method. Compared to conventional adaptive method, MCG have faster convergence rate than stochastic gradient (SG) method, and comparable convergence rate with recursive least square (RLS) method with lower complexity. And it simplifies the procedure of conjugate gradient method with one iteration per snapshots by using inexact line search scheme. Simulation has demonstrated the superior performance in output SINR and its convergence rate. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Beamforming

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Fair Incentive Allocation for Secure Data Sharing in Blockchain Systems: A Shapley Value Based Mechanism 3rd

Fair Incentive Allocation for Secure Data Sharing in Block...

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3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Yang, Ming Feng, Honglin Wang, Xin Jiao, Xuguo Wu, Xiaoming Qin, Shuwei Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China School of Information and Control Engineering Qingdao University of Technology Qingdao China State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Department of Public Security of Shandong Province Shandong Intelligent Public Security Joint Innovation Center Jinan China

ISBN: (纸本)9789819710829

In the contemporary era of information technology, the exponential surge in data has rendered colossal potential value, which would be fully unlocked through data circulation and sharing. However, when the data contains sensitive information, special attention must be paid to the data privacy and security problem for data sharing. A feasible solution is to incorporate blockchain technology into the data sharing system, and the new challenge is how to provide fair rewards for data owners to motivate them to contribute data. To address this challenge, in this paper, we first design a blockchain-based data sharing system to enhance the trust and reliability of the data shared among participants. Then we propose an incentive allocation method based on the Shapley value, which comprehensively incorporates each participant’s contribution while ensuring fairness for the allocation. Finally, multiple numerical simulations are conducted to validate the effectiveness of the proposed mechanism. © Beijing HIWING Scientific and Technological information Institute 2024.

关键词： Blockchain

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General Simultaneous Localization and Mapping Scheme for mmWave Communication Systems

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IEEE Internet of Things Journal 2024年第12期11卷 22521-22536页

作者： Du, Tao Yang, Jie Wen, Chao-Kai Xia, Shuqiang Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Southeast University Key Laboratory Of Measurement And Control Of Complex Systems Of Engineering Ministry Of Education The Frontiers Science Center For Mobile Information Communication And Security Nanjing210096 China Institute Of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan Zte Corporation The State Key Laboratory Of Mobile Network And Mobile Multimedia Technology Shenzhen518055 China Southeast University National Mobile Communications Research Laboratory The Frontiers Science Center For Mobile Information Communication And Security Nanjing210096 China

Utilizing high-resolution antenna arrays and wide bandwidth of the millimeter-wave (mmWave) spectrum in 5G new radio (NR) mmWave communication systems holds the potential for high-throughput data transmission while enabling user localization and environmental mapping. However, the majority of existing simultaneous localization and mapping (SLAM) algorithms rely on methods akin to the extended Kalman filter for generating initial map features. These methods prove ineffective when the measurement dimension is insufficient. Furthermore, there is a notable absence of research exploring mmWave prototype systems to evaluate and compare the performance and viability of various SLAM algorithms. To address these challenges, we propose an innovative probability hypothesis density (PHD) generation scheme for birth events and have developed a prototype system. Our approach, referred to as PHD-SLAM, exhibits remarkable effectiveness even in scenarios where the measurement dimension falls short of map features. This means it can function seamlessly with only delay or angle information available. Additionally, we have designed a 28GHz mmWave beam scanning prototype system that leverages the 5G NR frame for accomplishing SLAM algorithms. Following this, we conducted extensive simulations and experimental evaluations to gauge the performance of several leading-edge SLAM algorithms under diverse mmWave circumstances, encompassing PHD-based and belief propagation (BP) SLAM algorithms. Our analysis reveals that both PHD and BP SLAM can achieve agent localization precision within a decimeter and mapping precision within a meter, capitalizing on the angle parameters of mmWave signals. While BP SLAM showcases reduced computational demand, its estimation precision is marginally inferior to that of PHD-SLAM. © 2014 IEEE.

关键词： Belief propagation

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