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arXiv 2019年

作者： Li, Yinchuan Wang, Xiaodong Ding, Zegang School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing100081 China Electrical Engineering Department Columbia University New YorkNY10027 United States

In this paper, we consider a passive radar system that estimates the positions and velocities of multiple moving targets by using OFDM signals transmitted by a totally un-coordinated and unsynchronizated illuminator and multiple receivers. It is assumed that data demodulation is performed separately based on the direct-path signal, and the error-prone estimated data symbols are made available to the passive radar receivers, which estimate the positions and velocities of the targets in two stages. First, we formulate a problem of joint estimation of the delay-Doppler of reflectors and the demodulation errors, by exploiting two types of sparsities of the system, namely, the numbers of reflectors (i.e., targets and clutters) and demodulation errors are both small. This problem is non-convex and a conjugate gradient descent method is proposed to solve it. Then in the second stage we determine the positions and velocities of targets based on the estimated delay-Doppler in the first stage. And two methods are proposed: the first is based on numerically solving a set of nonlinear equations, while the second is based on the back propagation neural network, which is more efficient. The performance of the proposed passive OFDM radar receiver algorithm is evaluated through extensive simulations. Copyright © 2019, The Authors. All rights reserved.

关键词： Radar receivers

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Design and Optimization of Camera HAL Layer Based on Android 4th

Design and Optimization of Camera HAL Layer Based on Android

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

作者： Gan, Yu Hu, Wei Wang, Yonghao 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 Industria System Wuhan China Digital Media Lab Birmingham City University Birmingham United Kingdom

ISBN: (纸本)9783030341381

Nowadays, in the field of mobile and communication, with the rapid popularization and application of Internet and network, and the continuous expansion to the family field, the trend of integration of consumer electronics, computer and communication (3C) is becoming increasingly obvious, and embedded system naturally becomes a research hotspot. The embedded operating system Android has been widely used in mobile devices, such as smart phones, smart watches and so on. Our design is based on the Android platform to optimize and improve Camera HAL. This design is applied to the development of the Android system, the design of the Camera subsystem, the description of the Camera subsystem from the structure, function and data flow, and then proceed to structural optimization. This design uses TI AM335x as the hardware platform, based on Android system, designed and implemented the Android Camera hardware abstraction layer and Camera subsystem. At the end of the development, after the actual experimental test, the development of the system achieved the expected function and worked well. © 2019, Springer Nature Switzerland AG.

关键词： Cameras

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OPTICAL REMOTE SENSING WATER-LAND SEGMENTATION REPRESENTATION BASED ON PROPOSED SNS-CNN NETWORK

OPTICAL REMOTE SENSING WATER-LAND SEGMENTATION REPRESENTATIO...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Shan Dong Long Pang Yin Zhuang Wenchao Liu Zhanxin Yang Teng Long Engineering Center of Digital Audio and Video Communication University of China Beijing China School of Electronic Engineering and Computer Science Peking University Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

For water resource analysis applications, due to very high resolution and large observation scope, optical remote sensing images can present more visible object characters. Water-land segmentation from optical remote sensing images is wildly used and becomes a hot research topic. However, since large scale complex background scenes include many interferences, the water-land segmentation from optical remote sensing images becomes a challenge task. Aim to achieve better water area feature description from complex land cover background, we apply a sub-neighbor system convolutional neural network (SNS-CNN) to the water-land segmentation in harbor scene areas. First, on the basis of the U-net structure, an optimized up-sampling process is proposed to enhance water area feature expression. Second, a novel sub-neighbor system constraint of each predicted pixel point is leaded into the loss function to make the model producing water mask more coherent. Furthermore, experiments on our collected variety of optical remote sensing images demonstrate that this paper proposed water-land segmentation method can produce better performance than state of the art methods.

关键词： Image segmentation Convolution Remote sensing Optical imaging Optical sensors Feature extraction Convolutional neural networks

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A Network Pruning Method for Remote Sensing Image Scene Classification

A Network Pruning Method for Remote Sensing Image Scene Clas...

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

作者： Baogui Qi He Chen Yin Zhuang Shaorong Liu Liang Chen Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China School of Electronic Engineering and Computer Science Peking University Beijing China Beijing Institute of Spacecraft System Engineering Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Deep convolutional neural networks have been widely used to improve remote sensing image scene classification performance. However, most of these networks include many parameters and need many computational resources. Which hinders the applications of these networks when facing the satellite, plane or other mobile platforms. In this paper, we introduce a network pruning framework which can reduce the size of the network model and maintain the classification accuracy. In this framework, we train the pruned model using both the original unpruned model's output and training dataset. Which can learn more information than retrain using dataset only. In our experiments, we evaluate our method for remote sensing scene classification on NWPU-RESISC45 dataset. The results demonstrate that our method was effective and maintained the model classification accuracy.

关键词： pruning convolutional neural networks scene classification compression deep learning

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Image representation of GEO SAR time-variant scene 12

Image representation of GEO SAR time-variant scene

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12th European Conference on Synthetic Aperture Radar, EUSAR 2018

作者： Zhu, Yu Ke, Meng Zhang, Tianyi Li, Gen Ding, Zegang Beijing Institute of Spacecraft System Engineering CAST China Radar Research Lab School of Information and Electronics Beijing Institute of Technology China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Radar Research Lab School of Information and Electronics Beijing Institute of Technology China

ISBN: (纸本)9783800746361

Geosynchronous synthetic aperture radar (GEO SAR) is characterized by large coverage and short revisit time, and has great potentials for environment monitoring. The GEO SAR image of variant scene is obviously different from the traditional SAR image, because of the extremely long illumination time, which greatly increases the difficulty of SAR image interpolation. To further understand the GEO SAR images of the time-variant scenes, the geometry models and backscattering models of time-variant grassland and water surface are established. Furthermore, the GEO SAR images of them are obtained by simulation, which is benefit for the understanding of GEO SAR images. © VDE VERLAG GMBH Â Berlin Â Offenbach.

关键词： Synthetic aperture radar

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Beam scan mode analysis and design for geosynchronous SAR

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Science China(information Sciences) 2017年第6期60卷 72-84页

作者： Wei YIN Zegang DING Xiaojun LU Yu ZHU Beijing Key Laboratory of Embedded Real-time Information Processing Technology School of Information and Electronics Beijing Institute of Technology Beijing Institute of Spacecraft System Engineering Chinese Academy of Space Technology

The beam velocity of geosynchronous synthetic aperture radar(GEO SAR) varies seriously with the orbital position and the scene position, which leads to a significant variation of the scene length and the azimuth resolution in the stripmap(SM) mode. To obtain uniform scene length and azimuth resolution, beam scan modes can be utilized in GEO SAR, such as the sliding spotlight(SLL) mode and the terrain observation by progressive scans(TOPS) mode. However, the conventional design method of the beam scan mode is based on the straight line model(SLM), which does not consider the effects of the curved satellite track and the spherical earth surface. To solve this problem, a curvature circle model(CCM) is proposed considering the actual satellite-earth relationship. By using the CCM, the beam velocity after the beam scan is derived. The scene length and the azimuth resolution are analyzed. The SLL mode and the TOPS mode are recommended for GEO SAR. After that, a design method of the beam scan mode is proposed based on the CMM. The performance of the proposed method is verified by computer simulations.

关键词： GEO SAR beam scan mode design azimuth resolution scene length

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CONSTRAINED NONNEGATIVE MATRIX FACTORIZATION FOR ROBUST HYPERSPECTRAL UNMIXING

CONSTRAINED NONNEGATIVE MATRIX FACTORIZATION FOR ROBUST HYPE...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Fan Feng Chenwei Deng Wenzheng Wang Jiahui Dai Zhenzhen Li Baojun Zhao Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology China

Hyperspectral unmixng (HU) is an essential step for hyperspectral image (HSI) analysis. In real HSI, there often are abnormal fluctuations existing in specific bands, which can be described as sparse noise. This type of corruption will seriously disrupt the hyperspectral image quality, causing extra difficulties during unmixing process. However, the influence of sparse noise is often ignored by existing unmixing methods, which leads to the reduction of robustness and accuracy for HU tasks. Therefore, we propose a new unmixing model which takes noise corruption into consideration. By designing and imposing constraints considering the sparsity of noise, properties of endmember and abundance on nonnegative matrix factorization (NMF), the proposed method can resist the sparse noise and achieve more robust and accurate unmixing results. Adequate experiments have been conducted on both synthetic and real hyperspectral data. And the results confirm the superiority of proposed method compared to state-of-the-art methods.

关键词： Hyperspectral imaging Sparse matrices Robustness Task analysis Clustering algorithms

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An Automated FPGA-Based Fault Injection Platform for Granularly-Pipelined Fault Tolerant CORDIC

An Automated FPGA-Based Fault Injection Platform for Granula...

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IEEE International Conference on Field-Programmable technology (FPT)

作者： Yu Xie He Chen Yi-Zhuang Xie Chuang-An Mao Bing-Yi Li Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9781728102153

Augment of integration and complexity makes VLSI circuits more sensitive to errors. Also, soft errors caused by Single Event Upset (SEU) have become a significant threat to modern electronic systems. Therefore, the demand of high reliability on modern electronic systems keeps increasing. Aiming at reliability evaluation of fault tolerant very large scale integrated circuits implemented on SRAM-based FPGA, an automated fault injection platform via Internal Configuration Access Port (ICAP) for rapid fault injection is presented in this paper. We adopt a granularly-pipelined fault tolerant CORDIC processor as the Design Under Test (DUT), and a C++ script is deployed for the external fault injection control environment and automating the fault injection procedure. The proposed method can achieve quantities of repeating fault injection tests and is suitable for any fault tolerant design implemented in SRAM-Based FPGA.

关键词： Circuit faults Field programmable gate arrays Fault tolerance Fault tolerant systems Maintenance engineering Computer architecture C++ languages

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Correlation tracking via robust region proposals

arXiv

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arXiv 2018年

作者： Han, Yuqi Nan, Jinghong Zhang, Zengshuo Wang, Jingjing Zhao, Baojun Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

Recently, correlation filter-based trackers have received extensive attention due to their simplicity and superior speed. However, such trackers perform poorly when the target undergoes occlusion, viewpoint change or other challenging attributes due to pre-defined sampling strategy. To tackle these issues, in this paper, we propose an adaptive region proposal scheme to facilitate visual tracking. To be more specific, a novel tracking monitoring indicator is advocated to forecast tracking failure. Afterwards, we incorporate detection and scale proposals respectively, to recover from model drift as well as handle aspect ratio variation. We test the proposed algorithm on several challenging sequences, which have demonstrated that the proposed tracker performs favourably against state-of-the-art trackers. Copyright © 2018, The Authors. All rights reserved.

关键词： Aspect ratio

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A NOVEL HARBOR DETECTION METHOD BASED ON PATTERN CODING ALGORITHM

A NOVEL HARBOR DETECTION METHOD BASED ON PATTERN CODING ALGO...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Guanqun Wang Yin Zhuang He Chen Liang Chen Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

Harbor automatic detection is a scene interpretation in remote sensing image processing. Fast and accurate harbor detection can significantly improve the performance of inshore ship detection. In order to achieve harbor detection in complex remote sensing images, in this paper, a novel pattern coding algorithm is proposed. The proposed harbor detection method has three steps: First, the harbor water area is extracted by using the definition circle (DC) model. Secondly, pre-generated eight key patterns are multiplied with the local scenes, and the probability density function (PDF) of the multiplied local scene is recorded. Finally, the Euclidean distance between the eight patterns' PDFs and the original local scene's PDF is calculated, then compared with the threshold and coded, so as to realize the harbor area detection. Experimental results demonstrate that the novel method has outstanding performance on harbor area detection in complex broad width remote sensing images.

关键词： Remote sensing Feature extraction Probability density function Image segmentation Euclidean distance Image coding Encoding

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