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检索条件"机构=Key Laboratory of Embedded Real-Time Information Processing Technology"

共 977 条记录，以下是431-440 订阅

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The Analyses for Discretization behaviour of Line Segment Target in SAR Image

The Analyses for Discretization behaviour of Line Segment Ta...

引用

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

作者： Wei, Yangkai Zeng, Tao Chen, Xinliang Fan, Yujie Wen, Yuhan DIng, Zegang School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781728123455

Under the assumption of the point scattering model, traditional SAR imaging processing can depict the scattering features of the illuminated scene with a series of strong point scatterers. In the traditional SAR images, when the illuminated scene contains various line segment targets, only some line segment targets show line-segment-scattering features, whereas others are discretized into strong point scatterers. This discretization behaviour of line segment targets makes it difficult to interpret the factual geometrical structure of the line segment targets through SAR images. Unfortunately, neither the traditional point scattering model and imaging processing can provide a detailed analysis for the discretization behaviour of line segment targets. Hence, in this paper, we propose some detailed and comprehensible analyses for this problem from three aspects. First, by introducing the spatial spectrum analysis of SAR imaging, we provide an azimuth analysis for this problem from the perspective of the imaging system. Then, we analyse this problem from the range direction based on the high resolution range profile of received echo. Furthermore, through establishing a parametric model for the line segment targets, a comprehensive analysis for the problem is given based on the scattering features. Numerical simulation experiments demonstrate the effectiveness of our proposed analyses. © 2019 IEEE.

关键词： Synthetic aperture radar

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DDMA-MIMO Radar Maximum Unambiguous Velocity Extension Based on Global Optimization Phase Modulation

DDMA-MIMO Radar Maximum Unambiguous Velocity Extension Based...

引用

IEEE International Conference on Radar

作者： Hongfei Lian Fugang Lu Qiao Chen Jiamin Long Xueyao Hu Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China No. 203 Research Institute of China Ordnance Industries Xi'an China Beijing Science and Technology Ruixing Electronic Technology Co. Ltd Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781665468893

Doppler division multiple access (DDMA) waveform shows great orthogonality for multiple-input multiple-output (MIMO) radar. However, it leads to a serious velocity ambiguous problem and hinders its application in automotive radar. In this work, a maximum unambiguous velocity extension approach is developed for DDMA MIMO radar by using a global ergodic optimization phase modulation during transmission. To be specific, we take the cumulative sum of the peak amplitude difference of global as the optimization cost function to obtain modulation codes. Furthermore, a matched filter phase demodulation carried out at the receiver to determine the results of angle measurement and velocity expansion. Finally, the simulation analysis and real-data experiments demonstrate our approach effectively improves velocity ambiguity resolving capabilities of DDMA waveform and suitable for massive MIMO array in nowadays automotive radar.

关键词： Matched filters Codes Phase modulation MIMO radar Radar detection Radar Doppler radar

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Monopulse SAR angle measurement based on total variation and monotonic iterative algorithm

Monopulse SAR angle measurement based on total variation and...

引用

IET International Radar Conference 2018, IRC 2018

作者： Hu, Bingtao Li, Feng Beijing Key Laboratory of Embedded Real-time information Processing Technology Beijing100081 China Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing100081 China

Synthetic aperture radar (SAR) monopulse angle measurement is an adequate method of target angle measurement in low signal-to-clutter and noise ratio. However, there is a contradiction between the instantaneous angle measurement and the SAR coherent accumulation. In this study, the authors use the total variation method to solve the above problem, and propose the monotone iterative method to enhance the efficiency of the total variation method, which is verified in the simulation. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Angle measurement

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An Efficient Low Delay Task Scheduling Algorithm Based on Ant Colony System in Heterogeneous Environments 22

An Efficient Low Delay Task Scheduling Algorithm Based on An...

引用

22nd IEEE International Conference on High Performance Computing and Communications, 18th IEEE International Conference on Smart City and 6th IEEE International Conference on Data Science and Systems, HPCC-SmartCity-DSS 2020

作者： Yang, Pei Liu, Jing Chen, Cen Ding, Yucheng Deng, Chunhua Zeng, Zeng Wuhan University of Science and Technology College of Computer Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China Institute for Infocomm Research Singapore Hunan *** Interactive Entertainment Media Co Ltd Changsha China

ISBN: (纸本)9781728176499

Low delay is an important issue in a variety of applications on heterogeneous computing platforms. A great number of algorithms including heuristics as well as metaheuristics have been designed to minimize the completion time (i.e., makespan) of applications and achieved good results. However, the demand of high performance never stops. In this paper, we propose a new and efficient Ant-Colony based Low Delay Scheduling (ACLDS) algorithm to minimize the makespan of applications which can form directed acyclic graphs and are executed on a heterogeneous system. Simulated results show that our proposed algorithm is highly efficient in reducing makespan in comparison with state-of-The-Art scheduling algorithms. For instance, the reduction ratio can be up to 15.2174% for a Fast Fourier Transform (FFT) benchmark. © 2020 IEEE.

关键词： Scheduling algorithms

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THE DISTRIBUTED SAR IMAGING METHOD FOR CYLINDER TARGET

THE DISTRIBUTED SAR IMAGING METHOD FOR CYLINDER TARGET

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： Fan Yujie Chen Xinliang Wei Yangkai Ding Zegang Wang Yan Wen Yuhan Tian Weiming Beijing Key Laboratory of Embedded Real-time Information Processing Technology

Traditional SAR imaging methods are based on point target scattering model, hence are not capable of recovering the shapes of distributed targets such as cylinders. The cylinder target is usually shown as two endpoints in the traditional single-angle SAR images. However, the distributed SAR can provide multi-angle observation information of the cylinder target. To improve the SAR image quality, we propose a distributed SAR imaging method for the cylinder target with a sparse distributed SAR configuration. The proposed method reconstructs the cylinder target by estimating the parameters from the SAR image, and then identity the cylinder target from the distributed SAR echo. When positive decision is made, the shape of the cylinder target can be recovered with these parameters. Numerical simulations have been conducted to demonstrate the effectiveness of the proposed method.

关键词： Radar imaging Radar polarimetry Synthetic aperture radar Radar tracking Scattering Image reconstruction

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A Method for Fast Remote Sensing Images Classification

A Method for Fast Remote Sensing Images Classification

引用

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

作者： Li, Fengjiao Jing, Donglin Bi, Fukun Shi, Hao Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China School of Information Science and Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

ISBN: (纸本)9781728123455

Due to the characteristic of high score remote sensing images, such as large file, chaotic content and complex information, the demand for image classification speed and accuracy is increasing. In this paper, we combine the convolutional neural network and octave convolution to extract the complex high-order statistical properties of the image. We first analyze the more classical convolutional neural network, and use the octave convolution to make full use of the fine details of the changes of the high-frequency information of the remote sensing image. The memory and computing resources consumed are greatly reduced, and network optimization is performed. The test proves that the result is effective for speed and accuracy improvements. © 2019 IEEE.

关键词： Convolution

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Prediction of hot spots in protein-protein interaction by Nine-Pipeline & Ensemble Learning strategy

Prediction of hot spots in protein-protein interaction by Ni...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jing Hu Zonghao Li Xiaolong Zhang Nansheng Chen School of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Molecular Biology and Biochemistry Simon Fraser University BC Canada

ISBN: (纸本)9781665429825

This paper proposes a NPEL (Nine-Pipeline & Ensemble Learning) strategy based on machine Learning algorithm to predict protein-protein interaction hotspots by training amino acid composition, surface area, amino acid chains and other complex/interface-related structural information. We applied Random Forest, Linear Svm, KNN, Gaussian Naive Bayes, Multi-layer Perceptron Neural Network, Adaboost, XGBoost etc. nine machine learning algorithms combination into an independent pipeline to predict protein hot spots, and the final results are optimized through voting and stacking scheme. In the stacking result of XGBoost and Logistic Regression, the highest accuracy is 0.8462 and improve the indicators of the pipeline results greatly.

关键词： Proteins Drugs Training Protein engineering Machine learning algorithms Three-dimensional displays Pipelines

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Hybrid optimisation method of improved genetic algorithm and IFT for linear thinned array

Hybrid optimisation method of improved genetic algorithm and...

引用

IET International Radar Conference 2018, IRC 2018

作者： Wang, Zheng Sun, Yuze Yang, Xiaopeng Li, Shuai Beijing Key Laboratory of Embedded Real-time Information Processing Technology School of Information and Electronics Beijing Institute of Technology Beijing China Department of Electronic Engineering Tsinghua University Beijing China

The array thinning technique can greatly reduce the number of the array elements while keeping the performance of the array almost the same. However, the existing algorithms have slow convergence rates and are easy to fall into local optimum. To improve the optimisation performance, a hybrid method based on improved genetic algorithm (GA) and iterative Fourier transform (IFT) technique for linear thinned array is proposed in this study. The population is divided into improved GA group and IFT group according to the convergence of the population and different operations can be done paralleled to generate offspring in each iteration. In the improved GA processing, adaptive crossover rate and mutation rate are used. The mechanism that keeps the fill factor stable is removed for larger search range. The IFT processing is executed paralleled for fast convergence velocity. The proposed hybrid method can obtain the fast convergence velocity and avoid being trapped into the local optimum by the combination of the two approaches. Several examples are simulated to validate the performance of the proposed method. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Genetic algorithms

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Efficiency balanced matrix transpose method for sliding spotlight SAR imaging processing

Efficiency balanced matrix transpose method for sliding spot...

引用

IET International Radar Conference 2018, IRC 2018

作者： Sun, Tianyuan Xie, Yizhuang Li, Bingyi Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing100081 China

Matrix transposition is a very critical operation in synthetic aperture radar (SAR) imaging systems. This study presents an improved corner turning memory solution for real-time SAR imaging processing. Based on the sub-matrix three-dimensional mapping method, the efficiency of matrix transposing is greatly increased. However, in sliding spotlight mode, a novel SAR imaging mode, the amount of raw data is increased too large to directly use the above method. In this study, a joint address mapping strategy for two pieces of double data rate 3 synchronous dynamic random-access memory is used to meet the needs of the amount of data and make up for the lack of original method. The experimental results show that this method can get an improved and balanced two-dimensional access efficiency for sliding spotlight mode SAR imaging processing. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Mapping

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Target recognition in synthetic aperture radar image based on PCANet

Target recognition in synthetic aperture radar image based o...

引用

IET International Radar Conference 2018, IRC 2018

作者： Qi, Baogui Jing, Haitao Chen, He Zhuang, Yin Yue, Zhuo Wang, Chonglei Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China Shanghai Institute of Satellite Engineering Shanghai200240 China

Automatic targets recognition (ATR) for synthetic aperture radar (SAR) image is very important. ATR can be used in traffic management, national frontier safety, and so on. Traditional algorithms for SAR ATR is composed of extraction features and training classifier. The features are essential for the classification accuracy. However, choosing good features by hand is a hard task. The deep convolutional neural networks (CNNs) which can learn features automatically have got a great performance in natural images. However, the CNNs have many parameters and need a lot of data to train such networks. The remote-sensing data of SAR is limited. Then, the authors need a simple network which needs not much data and easy to train. The principal component analysis network (PCANet) is a shallow network that performs well in the recognition task and needs no hand features choosing. Though this network has produced a wide application in the natural images, it is rarely used in the SAR images. The experimental result of the moving and stationary target acquisition and recognition (MSTAR) dataset shows that the PCANet can achieve over 99% accuracy on ten-class targets. This result is better than traditional algorithms and is very close to the results of deep-learning methods. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Principal component analysis

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