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

作者： Zhang, Zipeng Tang, Linbo Tian, Yibing Pan, Yu Beijing Key Laboratory of Embeded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9781728123455

Unmanned aerial vehicles (UAVs) are now widely used in civil applications. Uncontrolled UAVs may cause some harm to the order of flight fields and other places. An adaptive UAV detection algorithm based on maximally stable extremal regions method is proposed for small target detection of UAV in video. By optimizing the MSER algorithm, this UAV detection algorithm can detect video in real time and has sufficient robustness. At the same time, we combined discriminative scale space tracker algorithm to test the existing video, and got good real-time performance. Considering the practical application scenarios, we use NVIDIA Jetson TX2 to test the algorithm and collate the results. The results show that our method performs well. © 2019 IEEE.

关键词： Antennas

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A novel word length optimization method for radix-2k fixed-point FFT

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Science China(information Sciences) 2018年第2期61卷 278-282页

作者： Chen YANG Yizhuang XIE He CHEN Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology

Dear editor,Fast Fourier transform(FFT)is one of the most fundamental algorithms used in digital signal *** applications such as orthogonal frequency division multiplexing(OFDM),long term

关键词： A novel word length optimization method for radix-2~k fixed-point FFT length

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Small targets recognition in SAR ship image based on improved SSD

Small targets recognition in SAR ship image based on improve...

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

作者： Li, Yong Chen, Jing Ke, Meng Li, Linghao DIng, Zegang Wang, Yan 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 Institute of Technology Beijing China

ISBN: (纸本)9781728123455

Synthetic Aperture Radar(SAR) ship recognition is significant in marine applications and plays an important role in maritime traffic management, fisheries management, and maritime rescue, etc. A major difficulty in SAR ship recognition is that the SAR ships have a small size in images, which results in low recognition accuracy of the SSD. This paper first analyzes the reasons for the low recognition accuracy for small targets in SSD. First, the poor matching of the default boxes leads to a small number of positive samples. Second, the representation ability of low-level feature map for recognizing small targets is weak. Then two strategies are proposed to improve the SSD. Firstly, a default box optimization design method based on Kmeans clustering is proposed, which improves the matching performance of the default boxes. Secondly, a feature fusion method based on deconvolution is proposed, which effectively improves the representation ability of low-level feature maps. The experimental results show that the proposed method can greatly improve the recognition accuracy of SSD for small targets in SAR ship images. © 2019 IEEE.

关键词： Synthetic aperture radar

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Remote Sensing Image Classification Based on Markov Random Field

Remote Sensing Image Classification Based on Markov Random F...

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

作者： Zhang, Tong Zhuang, Yin Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China School of Electronic Engineering and Computer Science Peking University Beijing China

ISBN: (纸本)9781728123455

With the continuous development of optical remote sensing technology, the segmentation of high resolution remote sensing images has become a hot research field. The high resolution and complex remote sensing images make the general natural image segmentation become a challenge task. Here, Markov random field (MRF) can well combine the spatial information of remote sensing image with the domain information between pixels for image segmentation, which is currently a hot research direction. In this paper, the wavelet and MRF are combined to achieve multi-scale analysis and produce more accurate segmentation results, the extensive experiments demonstrated that proposed method is more suitable for remote sensing image segmentation, and it provides a good boundary local mapping results and is robust with image non-stationary signal. In addition, in view of the disadvantage of fixed potential function parameters of traditional MRF, we put forward the method of variable weight. On this basis, Kullback-Leibler (KL) divergence is proposed to calculate the similarity between the segmented regions to further optimize the segmentation results. © 2019 IEEE.

关键词： Image segmentation

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Research on Infrared and Vsisible Image Fusion System

Research on Infrared and Vsisible Image Fusion System

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

作者： He, Xinxin Tang, Linbo Wu, Chen 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

ISBN: (纸本)9781728123455

Infrared and visible image fusion is an important branch of image fusion technology. By combining the image information of two different bands, the human eye or machine can detect the target more comprehensively, quickly and accurately, and image fusion can improve the ability of human vision to understand the scene, which has great application value in military and civilian fields. Therefore, the research of infrared and visible image fusion systems has important theoretical and practical significance. In this paper, the author takes infrared and visible images as the research object, expounds the basic theory of image fusion, designs the fusion algorithm and the system based on FPGA + ARM, and also gives the complete solution of image fusion system. The experimental results show that the image fusion system is built successfully, the system image fusion effect is good, and the real-time processing is realized. After further experiment and design optimization, the system can be applied in engineering. © 2019 IEEE.

关键词： Image fusion

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Research on parallel architecture design of radar real-time signal processing based on CPU-GPU heterogeneous platform 5

Research on parallel architecture design of radar real-time ...

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IET International Radar Conference 2020, IET IRC 2020

作者： Dong, Henan Zheng, Cheng Tian, Weiming 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

ISBN: (纸本)9781839535635

in view of the central processing unit (CPU) platform processing performance limits on computationally intensive tasks, as well as the FPGA + DSP[1-3] platform of software and hardware of high coupling and difficult defects, using the graphics processor (GPU) powerful parallel computing power, the CPU and GPU pipeline technology, heterogeneous systems with multithreading, GPU more and more flow, such as strategy, puts forward the real-time signal processing system of the multiple perspectives analysis methods, make full use of the independence between modules and signal processing algorithm concurrency features within the *** experimental results show that, compared with the traditional MATLAB platform, the maximum acceleration ratio based on CPU-GPU heterogeneous platform can reach more than 20000, and the parallel architecture designed can fully meet the real-time requirements of radar signal processing. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Graphics processing unit

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A fully coherent motion compensation method of ISAR imaging based on synthetic wideband PD radar

A fully coherent motion compensation method of ISAR imaging ...

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IET International Radar Conference 2015

作者： Fan, Hua-Yu Ren, Li-Xiang Zhang, Kang Mao, Er-Ke Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China Radar Research Lab. Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781849199940

In order to solve the problem of accurate motion compensation of ISAR imaging, and get high quality ISAR images, this paper proposes a fully coherent motion compensation method based on synthetic wideband PD radar. The method adopts phase derived velocity measurement (PDVM) based on range profile cross-correlation (RPCC) that enables it to accurately estimate the instantaneous target velocity, which is an important benefit of the excellent coherence charicteristics of the synthetic wideband PD radar. Applying the estimated velocity to envelope alignment and translational phase adjustment process of ISAR imaging, we finally get high quality ISAR images. The experimental results of ISAR imaging on aircrafts verify that the proposed method is effective.

关键词： Velocity measurement

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realization of Remote Sensing Image Classification Algorithm Based on SOPC

Realization of Remote Sensing Image Classification Algorithm...

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IET International Radar Conference 2023, IRC 2023

作者： Qi, Guijie Qiao, Tingting Xie, Yizhuang 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

ISBN: (纸本)9781839539954

Recently, Convolutional Neural Networks (CNNs) have made significant progress in the field of remote sensing image scene classification. However, commonly used CNN models are mainly deployed on GPU, which is bulky and power-hungry, making them unsuitable for customized requirements of on-board embedded applications. To meet the needs of on-board embedded applications, this study selects System On a Programmable Chip (SoPC), known for their low power consumption and compact size, as the processing platform for accelerating CNNs. Employing the knowledge distillation method, this paper uses the classical CNN scene classification algorithms to create lightweight models. These optimized models are then deployed on resource-constrained ZCU104 SoPC hardware platform. Experimental results demonstrate that the optimized lightweight models achieve image classification tasks with over 95% accuracy on SoPC hardware platform. Furthermore, due to minimal impact from quantization errors, the accuracy drop is less than 1%. Compared to GPU (GTX1650), the throughput on SoPC is increased by 96.43%. © The Institution of Engineering & technology 2023.

关键词： Convolutional neural networks

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Accurate slant range model in ground-based radar imaging of the lunar 5

Accurate slant range model in ground-based radar imaging of ...

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IET International Radar Conference 2020, IET IRC 2020

作者： Liu, Siyuan Ding, Zegang Li, Gen Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839535635

Ground-based radar imaging is an important approach for lunar observation. However, due to the long round-trip time delay and long integration time, the invalidation of "stop-and-go" hypothesis presents challenge to the radar imaging algorithms. In this paper, firstly, the accurate ephemeris of large-scale lunar surface is created based on the coordinate transformations. Secondly, considering the error of "stop-and-go" hypothesis, the accurate slant range model between the ground-based radar and lunar surface is presented. Finally, the simulation results are presented to verify the correctness of the ephemeris calculation, and demonstrate the slant range difference caused by the "stop-and-go" hypothesis. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Radar imaging

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The guided image filtering for speckle reduction in SAR images

The guided image filtering for speckle reduction in SAR imag...

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IET International Radar Conference 2015

作者： Shi, Hao Chen, Liang Mai, Zhi-Hong Chen, He Bi, Fu-Kun Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China College of Information Engineering North China University of Technology Beijing100144 China

ISBN: (纸本)9781849199940

The reduction of SAR image speckle noise is an important issue. However, the existing denoising methods may cause the resolution and details loss. This paper proposes a SAR image speckle reduction method based on the guided image filtering. This method combines the edge-preserving property of guided filtering and can maintain the detail information meanwhile suppressing the speckle. Experimental results show that the proposed method can effectively reduce speckle and keep the polarization information, point targets and texture structure. Meanwhile, it is able to handle large SAR images simply and effectively.

关键词： Synthetic aperture radar

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