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

共 577 条记录，以下是321-330 订阅

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Spaceborne Large-Squint Terrain-Matching Synthetic Aperture Radar: Concept and technology

Spaceborne Large-Squint Terrain-Matching Synthetic Aperture ...

引用

Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Yan Wang Zhe Li Zegang Ding Tao Zeng Radar Research Lab Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

This paper discusses a new spaceborne large-squint terrain-matching synthetic aperture radar (LSTM-SAR) to effectively image the terrains that do not spread along satellite orbit. Different from the traditional spaceborne SAR, the swath of the LSTM-SAR spreads along the target terrain, instead of the satellite orbit, to perform terrain-matched imaging with both high resolution and short data acquisition period. Aiming at giving a sketch of how the LSTM-SAR works, the paper focuses on discussing the following three main aspects: the data acquisition geometry, azimuth sampling manner and raw data focusing algorithm. Specifically, an optimum squint geometry is firstly suggested for two dimensional swath optimization; then two non-uniform azimuth sampling methods are discussed to avoid data loss induced by transmission blockage; lastly, a wide nonlinear chirp scaling based algorithm is discussed to focus the spatially variant spaceborne LSTM-SAR echo. The presented approach is validated via the computer simulations.

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Ultrasound vascular image segmentation based on full convolutional aggregation neural network 3

Ultrasound vascular image segmentation based on full convolu...

引用

3rd International Conference on Computer Science and Artificial Intelligence, CSAI 2019 and its Workshop - The 11th International Conference on information and Multimedia technology, ICIMT 2019

作者： Li, Yan Liu, Jun Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial Department of Computer Science and Technology Wuhan University of Science and technology Wuhan430070 China

ISBN: (纸本)9781450376273

The concept of ultrasound therapy has been proposed long ago. However, most of the previous methods of ultrasound therapy destroy tissue through thermal effects and cause great damage to patients. In recent years, ultrasound cavitation therapy has caused extensive discussion and research due to its unique noninvasiveness. In order to achieve real-time access to the patient during treatment, the lesion area must be processed simultaneously and accurately. However, ultrasound images mostly have lower signal-to-noise ratio, contrast, and blurred edges. In order to solve the segmentation problem, this paper proposes a new segmentation model Du-net based on the full convolutional neural network. Under the premise of deepening the network depth to obtain more information, the Encoder- Decoder method and the layered aggregation mode are used to prevent the gradient explosion. Solving boundary segmentation problem by constructing joint network, In the case of a small data set, the data enhancement method using a suitable data set effectively increases the usable image features and achieves better results on the ultrasound blood vessel image. © 2019 Association for Computing Machinery.

关键词： Convolution

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Multi-channel RF signal acquisition system design based on AD9361

Multi-channel RF signal acquisition system design based on A...

引用

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

作者： Ce Wang Shanqing HU Xingming LI Yingying Chen Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of technology Beijing Racobit Electronic Information Technology Co. Ltd

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

The modern communication and radar systems has been faced with the constraint of size, weight and power (SWaP), and this also goes for their front-end acquisition systems. Currently, the AD9361 RF transceiver has been gradually employed due to its low cost and low power. However, its internal PLL mode can't support the fast frequency hopping because its time-cost calibration period, and also it doesn't support the multi-channel RF synchronization. Therefore, the AD9361 is unsuitable for some applications with severe requirements on phase and frequency hopping speed. In this paper, we proposed a fast frequency hopping technique by employing configurable external oscillator, and proposed a multi-channel phase synchronization technique based on phase pre-calibration. The techniques are validated on a 16-channel AD9361 acquisition system and the result show the design provides a reference for system design under the SWaP constraint.

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Experiment and Results of bistatic UAV SAR

Experiment and Results of bistatic UAV SAR

引用

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

作者： Meng Ke Youwang Chen Yong Li Linghao Li Feifeng Liu Zegang Ding School of information and Electronics Beijing Institute of Technolog Beijing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

This paper introduces the bistatic UAV SAR experiment conducted in June 2018. The UAV platforms have limited load and space, which is a great challenge for synchronization. To meet the requirement, a very small atomic clock and direct signal were used for synchronization in this experiment. The imaging results proved the feasibility of this synchronization scheme.

关键词： experiment bistatic UAV SAR synchronization

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Terminal bulb segmentation of caenorhabditis elegans under small samples based on two-stage u-net network 3

Terminal bulb segmentation of caenorhabditis elegans under s...

引用

3rd International Conference on Computer Science and Artificial Intelligence, CSAI 2019 and its Workshop - The 11th International Conference on information and Multimedia technology, ICIMT 2019

作者： Cao, Si Liu, Jun Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial Department of Computer Science and Technology Wuhan University of Science and technology Wuhan430070 China

ISBN: (纸本)9781450376273

Convolutional neural network based on machine learning has become one of the most popular methods of image recognition and segmentation, but it needs huge data samples to get better results. In this study, based on U-Net network, a two-stage convolution neural network method for automatic segmentation of Terminal bulb of Caenorhabditis elegans in small samples was proposed. The method solves the problem that traditional singlestage network cannot be implemented in small samples. The Dice coefficient reaches 89.5%, which is higher than that of the baseline U-Net method. © 2019 Association for Computing Machinery.

关键词： Computer vision

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Early Detection of Forest Fire Based on Unmaned Aerial Vehicle Platform

Early Detection of Forest Fire Based on Unmaned Aerial Vehic...

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

作者： Xingsha Yang Linbo Tang Hongshuo Wang Xinxin He Beijing Key Laboratory of Embedded Real-time Information Processing Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

As a kind of natural resources, forest is vital to our survival. Once the fire happening in forest is not found in time, it can cause a huge loss. Accurate real-time monitoring of forest fires is not only an important part of forest fire prevention, but also an important means to effectively control the spread of forest fires and reduce economic losses. Forest areas are often geographically widely distributed and inefficient in manual inspections. Therefore, we need a highly mobile early forest fire warning system to ensure the safety of forest resources. UAVs serve as a highly mobile inspection tool to meet inspection requirements of forest fires. Besides, the early flame characteristics are not obvious, and the single source fire detection is easy to false alarm. In view of this, we propose a forest fire detection method that uses optical images to detect smoke and infrared images to detect fire.

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A Method for High-Speed and Maneuvering Range-Spread Target Detection

A Method for High-Speed and Maneuvering Range-Spread Target ...

引用

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

作者： Pengjie You Zegang Ding Lichang Qian Xu Zhou Yangkai Wei Siyuan Liu 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: (数字)9781728123455

ISBN: (纸本)9781728123462

When detecting range-spread target (RST) with multiple pulses, two phenomena may greatly deteriorate the detection performance. On the one hand, the target scatterers disperse in several range units, which makes the signal to noise ratio (SNR) become lower. On the other hand, high-speed and maneuvering RSTs can easily cause the across-range-unit and across-Doppler-unit effects, which limits the integration gain along slow time. In this paper, a detector is proposed to solve the two problems. The proposed detector first employs generalized Radon-Fourier transform (GRFT) to coherently integrate multiple pulses and then implements noncoherent integration for integrating the energy in different range units. Experiments demonstrate that the proposed detector outperforms the energy integration based keystone transform detector in both detection and velocity resolution performances, and the proposed detector also achieves better detection performance than GRFT for the RSTs without dominant scatterer.

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Multi-sensor Image Stitching and Fusion Based Air Infrared Target Cooperative Detection

Multi-sensor Image Stitching and Fusion Based Air Infrared T...

引用

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

作者： Jinghong Nan Baojun Zhao Tingting Cui Yongfeng Xie Beijing Institute of Aerospace Systems Engineering Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Robust and efficient air infrared small target detection is widely used in reconnaissance and early warning system. However, there exist two critical difficulties, i.e., the limited detection range and the poor detection performance of single infrared sensor. To overcome those difficulties, in this paper, we propose a novel cooperative detection method of multiple infrared sensors for air small target. Specifically, a multiscale block local contrast measurement method is introduced to achieve the target detection of each infrared sensor. Afterwards, a double-layer ring grid corner feature extraction method is proposed to achieve the image stitching accurately between multiple infrared sensors. In addition, the gray correlation analysis with position constraint based feature level fusion method is exploited to match targets in different sensors. Experimental results on testing image sequences demonstrate that the proposed method can improve the detection rate and reduce the false alarm rate effectively on the condition of limited detection range of each single sensor.

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A Novel CNN Architecture on FPGA-based SoC for Remote Sensing Image Classification

A Novel CNN Architecture on FPGA-based SoC for Remote Sensin...

引用

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

作者： Na Zhang Hao Shi Liang Chen Tong Lin Xin Shao Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China Beijing Racobit Electronic Information Technology Co. Ltd Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

The convolutional neural network (CNN) has achieved extraordinary results for image classification and recognition in-orbit satellite remote sensing applications. However, the implementation of CNN is difficult due to the increasing computational accuracy and complexity of CNN and the special working environment for satellites in orbit. A promising solution for this problem is field-programmable gate array (FPGA) due to its sufficient supporting for parallel computing with low power consumption. And system-on-chip (SoC) is a system that supports parameter reconfiguration. Hence, through applying the Lenet-5 based remote sensing image classification method to SoC, we propose several network mapping methods to reduce the resource consumption and enhance the computational efficiency of FPGA, then, we utilize the proposed methods to design several key modules for the implementation of CNNs, i.e., the convolution module, sigmoid module, pooling module, full connected module, system control module, on-chip cache model, and off-chip DRAM module. The test results show that the proposed hardware system architecture can implement Lenet-5 network and realize the realtime requirements of the system.

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Dual Polarimetric HRRP Sequence Recognition Based on $H/\alpha$ Features

Dual Polarimetric HRRP Sequence Recognition Based on $H/\alp...

引用

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

作者： Liang Zhang Teng Long Yang Li Yanhua Wang Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Dual polarimetric high resolution range prole (HRRP) is able to provide polarimetric and high resolution scattering characteristics information of radar target, which are very useful for automatic target recognition (ATR). In this paper, a novel feature extraction method, which combines both polarimetric and high resolution information, is proposed for dual polarimetric HRRP sequence based on H/α decomposition. In this method, the H/α decomposition is applied on HRRP sequence by temporal average instead of traditional spatial average, which retains the full resolution of HRRP data and provides efficient polarimetric characteristics information of target scattering centers. This paper also presents a scattering mechanisms classification method using the extracted H and α features, and analyzes the effect of noise and clutter on the two features as well as classification performance. The application and effectiveness of the proposed method are demonstrated via outfield experiments. Results show that scattering mechanisms and structural components of a volumetric target are recognized over high resolution range cells, and the proposed method is able to provide support for HRRP sequence-based radar ATR.

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