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

作者： Hongyu Wang Xinkun Yang Yang Li 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

An anti-retransmitted jamming technique is proposed by utilizing phase and frequency-coded waveform techniques. To generate the effective agility waveforms, improved Logistic-Map chaotic sequences generation and optimization algorithm are proposed to obtain sets of orthogonal polyphase codes. The simulated ambiguity function of the agility waveform shows that the agility waveform presents a high resolution in the range domain. The performance of the waveform under different signal-to-interference ratios(SIR) is analyzed. Compared to conventional LFM waveforms, the agility waveform is capable of suppressing the retransmitted jamming effectively, by up to 30dB when the SIR is -5dB.

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INSHORE SHIP CHANGE DETECTION BASED ON SPATIAL-TEMPORAL SALIENCY

INSHORE SHIP CHANGE DETECTION BASED ON SPATIAL-TEMPORAL SALI...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Long Ma Wenchao Liu Zhong Han Jue Wang He Chen School of Information Engineering Zhengzhou University Zhengzhou China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

Automatical inshore ship change detection in optical remote sensing images is meaningful for a wide range of applications, but still a challenging task. In this paper, a visual search inspired model is proposed for inshore ship change detection. The proposed model achieves inshore ship change information extraction based on spatial-temporal saliency detection which mimics visual search mechanism. Experimental results performed on a Google Earth optical remote sensing image data set demonstrate the effectiveness of the proposed model in terms of visual and objective evaluations.

关键词： Marine vehicles Data mining Visualization Image segmentation Remote sensing Task analysis information retrieval

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Aircraft detection in Remote Sensing image for Space-borne platform

Aircraft detection in Remote Sensing image for Space-borne p...

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

作者： Wei Tang Baozhao Jun Linbo Tang Yu Pan Dongling Jin Zhengpiao Quan Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Aircraft detection in optical remote sensing image is an important research direction in the field of remote sensing. The existing detection methods are difficult to achieve satisfactory results. Traditional detection methods are low robustness, due to manual feature modeling are difficult and subject to background interference; The deep learning target detection method, which improves the detection performance at the cost of complexity improvement, cannot be widely used in space-borne platforms limited resources. In view of the above problems, this paper proposes an aircraft target deep learning detection method of lightweight and multi-scale features. On the basis of the multi-scale target detection framework (SSD), the method firstly uses the dense connection structure and the double convolution channels to form the basic backbone networks with feature reuse and high computational efficiency. To improve the detection performance of the small aircraft target, the basis backbone network connects a residual module and deconvolution to compose the multi-scale feature fusion detection module. Compared with the current classical deep learning object detection methods, the experimental results show that the proposed method has the advantages of maintaining low computational complexity and achieving high detection accuracy.

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real-time Remote Sensing Video Compression for On-orbit Heterogeneous Platform

Real-time Remote Sensing Video Compression for On-orbit Hete...

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

作者： Chenhui Duan Linbo Tang Chen Wu Cheng Li Chen Li Baojun Zhao Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China School of Computer Science North China University of Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

With the rapid advancement of optical remote sensing (RS) satellites, RS video has replaced RS image as the main way to obtain information in orbit environment. However, the storage and transmission of on-orbit RS video faces enormous challenges: the contradiction between limited power, space and bandwidth and massive video data volume is becoming increasingly acute. To solve this problem, this paper proposes an effective implementation of spaceborne real-time RS video compression based on CPU+GPU heterogeneous framework. First, we propose a new rate control method based on HEVC for on-orbit RS video compression, which allocates less bitrate for low complexity code blocks (CBs) and more bitrate for high complexity CBs, which can improve the accuracy of rate control algorithm while ensuring compression quality. Then this paper makes full use of the CPU + GPU heterogeneous framework to speed up the whole compression processing. The experimental results show that the proposed compression framework realizes 200x real-time compression of 1080p spaceborne RS video with a PSNR greater than 38.7 dB.

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The Reconfigurable Pipelined Variable-point FFT Processor Design

The Reconfigurable Pipelined Variable-point FFT Processor De...

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

作者： Jiale Wang Yizhuang Xie Bingyi Li Chen Yang Shankang Hu 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

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

In the multi-mode SAR imaging processing targeted in this paper, the FFT requirement granularity ranges from 1024 to 32768. Therefore, this paper mainly describes the method of implementing reconfigurable and variable-level FFT units using radix-2 k , By analyzing and comparing the radix 2 k algorithm, the radix-2 3 is selected as the basis of the single-channel FFT butterfly, and the range of the point representation is extended by the butterfly transformation downward compatible with the radix-2 2 /radix-2. This paper realizes an architecture of the single channel delay feedback variable-point, high precision FFT processor.

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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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SAR Image Scattering Center Estimation via Atomic Norm Minimization

SAR Image Scattering Center Estimation via Atomic Norm Minim...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Ying Xi Haibo Liu Yanhua Wang Yang Li Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

Scatter center matching is one of the choke points of radar automatic target recognition (RATR) based on Synthetic Aperture Radar (SAR). Accuracy of scattering center extraction is an important factor affecting target recognition performance. This paper proposes a SAR images scattering center estimation method based on atomic norm minimization (ANM) model. This method models the scattering center estimation problem as a two-dimensional line spectrum estimation problem, then the estimation is performed in a continuous domain via ANM. The experimental results indicate the superiorities of the proposed method in terms of accuracy and robustness.

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A real-time Visual UAV Detection Algorithm on Jetson TX2

A Real-time Visual UAV Detection Algorithm on Jetson TX2

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

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

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

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.

关键词： UAV maximally stable extremal regions real time discriminative scale space tracker

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A novel DEM reconstruction strategy based on multi-frequency In SAR in highly sloped terrain

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Science China(information Sciences) 2017年第8期60卷 243-245页

作者： Tao ZENG Tiandong LIU Zegang DING Qi ZHANG Zhen WANG Teng LONG Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology

Interferometric Synthetic Aperture Radar(InSAR)has been proposed as a technique for the reconstruction of the Digital Elevation Model(DEM),which is widely used in global terrain mapping mission[1].The DEM reconstruction methods of In SAR technique are usually based on the so-called phase unwrapping(PU)*** highly sloped terrain,the interferometric phase gradients(IPG)of the adjacent pixels are more thanπ.Therefore,the traditional PU methods

关键词： SAR In of DEM IPG on Figure LAPS A novel DEM reconstruction strategy based on multi-frequency In SAR in highly sloped terrain

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

作者： Yong Li Jing Chen Meng Ke Linghao Li Zegang Ding Yan Wang 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: (数字)9781728123455

ISBN: (纸本)9781728123462

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 a bility 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.

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