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Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Xing Feng Mingfei Jia He Chen Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Convolutional Neural Network (CNN) is an algorithm widely used in the field of deep learning. Due to the large number of intensive parallel data operations, the use of CPU to implement the CNN serially consumes too much time. In view of the above research background, the System-on-a-Programmable-Chip (SOPC) implementation and acceleration modules of CNN are designed by using the Zynq-7035 development platform launched by Xilinx as the experimental platform. The experiment results show that our method is effective and efficiency for the target image classification on the development platform.

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Ship Detection in Synthetic Aperture Radar Imagery Based on Discriminative Dictionary Learning

Ship Detection in Synthetic Aperture Radar Imagery Based on ...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Yun Wang Liang Chen Hao Shi Bocheng Zhang Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

The ship target detection technology based on SAR image has important significance in military and civil field applications and is one of the research hotspots at this stage. In this paper, the research work on typical problems in SAR image ship target detection is carried out. A ship target detection algorithm based on discriminative dictionary learning is proposed, which mainly includes image denoising, candidate region extraction and candidate region identification. Firstly, an adaptive non-local filtering method is used to denoise the SAR image. Then the gradient feature map reconstruction algorithm is used to extract the candidate regions. Finally, the category constrained discriminative dictionary learning method is used to classify the candidate regions. The algorithm is based on GF-3 and Terra SAR data. The experimental results show that the proposed algorithm has strong robustness and adaptability.

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Radar HRRP recognition based on CNN

Radar HRRP recognition based on CNN

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IET International Radar Conference 2018, IRC 2018

作者： Song, Jia Wang, Yanhua Chen, Wei Li, Yang Wang, Junfu Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China Beijing Racobit Electronic Information Technology Co. Ltd. Beijing China

In this study, ground target recognition based on one-dimensional convolutional neural network (CNN) is studied by exploiting the targets' high-resolution range profiles (HRRPs). Contrary to conventional methods which need feature extraction artificially, CNN can automatically discover features for classification. The authors propose a multi-channel CNN architecture that can be applied on diverse forms of HRRP such as amplitude, complex, spectrum etc. Experimental results demonstrate the superiorities of the proposed method over conventional methods based on handcrafted features and single-channel CNN in terms of recognition accuracy. Visualisation of the 'deep features' shows higher separability than handcrafted features, thus providing an insight into its effectiveness in exploiting the intrinsic structures. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Radar target recognition

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Compressive Multidimensional Harmonic Retrieval with Prior Knowledge

Compressive Multidimensional Harmonic Retrieval with Prior K...

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2019 IEEE International Conference on Signal, information and Data processing, ICSIDP 2019

作者： Li, Yinchuan Zhang, Xu DIng, Zegang Wang, Xiaodong School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China Electrical Engineering Department Columbia University New York United States Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781728123455

This paper concerns the problem of estimating multidimensional (MD) frequencies using prior knowledge of the signal spectral sparsity from partial time samples. In many applications, such as radar, wireless communications, and super-resolution imaging, some structural information about the signal spectrum might be known beforehand. Suppose that the frequencies lie in given intervals, the goal is to improve the frequency estimation performance by using the prior information. We study the MD Vandermonde decomposition of block Toeplitz matrices in which the frequencies are restricted to given intervals. We then propose to solve the frequency-selective atomic norm minimization by converting them into semidefinite program based on the MD Vandermonde decomposition. Numerical simulation results are presented to illustrate the good performance of the proposed method. © 2019 IEEE.

关键词： Frequency estimation

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Cascaded Kalman filter for target tracking in automotive radar

Cascaded Kalman filter for target tracking in automotive rad...

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IET International Radar Conference 2018, IRC 2018

作者： Li, Yang Liang, Can Lu, Man Hu, Xueyao Wang, Yanhua Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China Beijing Racobit Electronic Information Technology Co. Ltd. Beijing China

In automotive anti-collision radar system, the accuracy of velocity is one of the key indicators to measure radar performance. For frequency modulation continuous wave radar with chirp sequence, which is commonly used in automotive radar, there are two problems that are velocity ambiguity and measurement error. In order to address these problems, a cascaded Kalman filter algorithm is proposed in this article, which is able to overcome velocity ambiguity and improve the accuracy of measurements. In addition, the problem of velocity ambiguity can be solved just in the data processing and it avoids transmitting staggered or multiple pulse repetition frequency signal. The simulation results show that this algorithm can effectively improve the tracking performance. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Data handling

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Design and Implementation of Small-scale Sensor Network Based on Raspberry Pi 4th

Design and Implementation of Small-scale Sensor Network Base...

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4th International Conference on Smart Computing and Communications, SmartCom 2019

作者： Zheng, Honglei Guo, Hong Wu, Shimin College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China

ISBN: (纸本)9783030341381

With the development of modern technology, embedded technology has continued to develop. In the deep cooperation between embedded and wireless network technologies, the technology of sensor network has been born. The software system based on traditional wireless network cannot collect data in the real world. In some production environments, the embedded sensor network consists of a large number of sensor nodes, integrating sensing, acquisition, processing, and transceiving functions into an autonomous network system to achieve dynamic and intelligent collaborative sensing of the physical world. Based on the existing wireless sensor network system architecture, this paper designs and implements a small-scale sensor network system based on Raspberry Pi. After the software and hardware test of the sensor network system, the test results show that the system can complete the information collection and transmission, and has stability and synchronization to meet project requirements and stability requirements. © 2019, Springer Nature Switzerland AG.

关键词： Sensor nodes

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Speckle tracking motion estimation based on shear wave imaging 2

Speckle tracking motion estimation based on shear wave imagi...

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2nd IEEE International Conference on information Systems and Computer Aided Education, ICISCAE 2019

作者： Song, Yuqin Liu, Jun Wuhan University of Science and Technology School of Computer Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing Real-time Industrial System Wuhan China

ISBN: (纸本)9781728130668

In the study of ultrasonic elastography, displacement estimation is the most critical step. Aiming at the inefficiency of ultrasonic elastography in estimating tissue displacement and the two kinds of waveforms of ultrasonic propagation in media, a speckle tracking motion estimation based on shear wave imaging is proposed. The motion estimation of shear waves is studied by calculating the displacement using the time-domain cross-correlation. The simulation results show that the proposed algorithm is efficient and feasible. © 2019 IEEE.

关键词： Motion estimation

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Trajectory optimisation design of robot based on artificial intelligence algorithm

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International Journal of Wireless and Mobile Computing 2019年第1期16卷 35-40页

作者： Huang, Li Zhang, Kai Hu, Wei Li, Chengcheng College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan430081 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Hubei Wuhan430081 China

Artificial intelligence has attracted more and more attention and has been widely used in all walks of life, especially in the education industry;artificial intelligence has gradually become the core. Aiming at the problem of robot trajectory planning in artificial intelligence, this paper applies the project teaching method to the course of artificial intelligence, regards trajectory planning as a project, analyses and studies it, uses ant colony algorithm to find the optimal planning path. Through the teaching of the project, the students will understand the ant colony algorithm more deeply. The algorithm is programmed independently to achieve the final trajectory optimisation. Students become the main body of the classroom, give full play to the initiative and enthusiasm of the students, through the operation of the project to train the students' innovative ability and cooperation ability, and improve the overall quality of the college students. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Students

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Cloud detection from visual band of satellite image based on variance of fractal dimension

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Journal of Systems Engineering and Electronics 2019年第3期30卷 485-491页

作者： TIAN Pingfang GUANG Qiang LIU Xing School of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-Time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-Media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

Cover ratio of cloud is a very important factor which affects the quality of a satellite image, therefore cloud detection from satellite images is a necessary step in assessing the image quality. The study on cloud detection from the visual band of a satellite image is developed. Firstly, we consider the differences between the cloud and ground including high grey level, good continuity of grey level, area of cloud region, and the variance of local fractal dimension (VLFD) of the cloud region. A single cloud region detection method is proposed. Secondly, by introducing a reference satellite image and by comparing the variance in the dimensions corresponding to the reference and the tested images, a method that detects multiple cloud regions and determines whether or not the cloud exists in an image is described. By using several Ikonos images, the performance of the proposed method is demonstrated.

关键词： cloud detection visual image satellite image variance of local fractal dimension (VLFD)

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FPGA-based reconfigurable matrix inversion implementation for inverse filtering of multichannel SAR imaging

FPGA-based reconfigurable matrix inversion implementation fo...

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IET International Radar Conference 2018, IRC 2018

作者： Li, HuiXing Feng, YangKai Hu, ShanQing Li, BingYi Xie, YiZhuang Wu, MengChao Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China Shanghai Institute of Satellite Engineering Shanghai China

In multi-channel synthetic aperture radar (SAR), the azimuth non-uniform sampling tends to result in a large number of virtual point targets, which are not expected. Inverse filter algorithm provides a new idea for solving this problem. This way can be abstracted as a matrix inversion in essence, which becomes the key factor that affects the real-time and accuracy of multi-channel pre-processing. This study presents the implementation of matrix inversion method on field programmable gate array (FPGA), based on lower and upper triangular matrix (LU) decomposition algorithm. In this process, the efficient parallelism of FPGA and the rich floating-point intellectual property (IP) cores are fully utilised to speed up the process of inverting the matrix with a data type of 32-bit single-precision floating-point. In this design, the parallelism of the algorithm was fully considered and a hierarchical iterative processing strategy was adopted to realise the reconfigurable storage and computing unit both. At the same time, in order to achieve the balance of resources and efficiency, a reusable structure was proposed also, using the pipeline technology and appropriate data scheduling. Finally, Modelsim platform is used to observe the simulation results, and the performance can be detected combined with MATLAB platform. At last, the computational accuracy is up to 10−7, and the speedup ratio can reach about 1.461 × 103 © This is an open access article published by the IET under the Creative Commons Attribution License (http://***/licenses/by/3.0/)

关键词： MATLAB

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