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

作者： Wang, Zhiru Chen, Liang Qi, Baogui Wang, Guanqun Shi, Hao Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9781728123455

Synthetic aperture radar (SAR) image target recognition is a hot issue in remote sensing image application. High accuracy SAR target recognition is truly important in both military and civilian fields. Recently, convolutional neural networks (CNNs) have played an important role in the field of SAR image target recognition, however, most of the existing networks incurs some additional problems such as ignoring the influence of speckle noise on the target recognition process, so the recognition accuracy is low. To cope with these problems, this paper proposes a novel SAR image target recognition method based on CNN with frequency and spatial domain enhancement. First, the image is transformed by Gabor feature descriptor in different frequency directions to generate a plurality of feature maps. Then, the image is spatially enhanced using a Laplace transform. The feature maps which obtained by the frequency and spatial domain enhancement together with the original image are used as the network input. Finally, the improved deep residual network (ResNet) is used to complete the target recognition task. Experimental results demonstrate that the proposed method achieves a state-of-the-art accuracy on the MSTAR dataset. © 2019 IEEE.

关键词： Synthetic aperture radar

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Research on Crop Planting Area Classification from Remote Sensing Image Based on Deep Learning

Research on Crop Planting Area Classification from Remote Se...

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

作者： Huang, Yun Tang, Linbo Jing, Donglin Li, Zhen Tian, Yibing Zhou, Shichao Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9781728123455

Remote sensing technology is widely used in agriculture monitoring because of the advantages of large-area simultaneous observation, low cost and dynamic monitoring of time and space. However, a manual visual interpretation method is often used to extract the information behind the remote sensing images, which is time and labor consuming. Moreover, handcraft features such as texture and structure of crop images are applied to classify crop planting area while these features are not robust. In order to reduce the cost and enhance the classification accuracy, we improved the state-of-the-art image semantic segmentation network SegNet in crop planting area classification which can speed up the convergence and reduce the model size largely with small gains in accuracy. The experiment result shows that the classification accuracy of the improved SegNet is slightly increased compared with SegNet, and the computational cost (FLOPs) of the improved SegNet is much less than SegNet. © 2019 IEEE.

关键词： Remote sensing

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Ground Target Automatic Recognition and Tracking in Complex Battlefield Environment

Ground Target Automatic Recognition and Tracking in Complex ...

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

作者： Wu, Chen Tang, Linbo Duan, Chenhui Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9781728123455

With the developments of science and the changes of modern warfare modes, the precise guidance and attack towards hostile targets in complex battlefield environments has extremely important military needs and research significance. However, the existing guidance mode is often constrained by factors such as battlefield background interference, target appearance variation and limited data links, which in turn affects tracking and strike performance. To this end, we present an integrated recognition and tracking scheme for the ground targets in complex battlefield environment. Specifically, with the missile-target distance information, we design an adaptive scale estimation scheme to tackle the aspect ratio variation during tracking. Furthermore, an efficient tracking monitoring index is advocated to judge the tracking condition as well as forecast the potential tracking failure. Once tracking failure is determined, a deep-learning based detection module is activated to re-detect the target as well as correct the tracking drift. In the strike stage of the mission, the key region of the hostile target would be identified and locked by the missile in order to maximize the attack effect. The proposed recognition and tracking scheme are tested upon extensive actual videos and achieved a tracking accuracy over 85%, which demonstrates its effectiveness as well as provides a novel solution for accurate and robust attack on enemy targets in a complex battlefield environment. © 2019 IEEE.

关键词： Object detection

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Modeling and Analysis of the Impacts of Temporal-Spatial Variant Troposphere on Ground-Based SAR Imaging of Asteroids

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Journal of Beijing Institute of technology 2023年第6期32卷 727-739页

作者： Tingting Fu Yuanhao Li Zhiyang Chen Zheng Wu Cheng Hu Radar Research Laboratory School of Information and ElectronicsBeijing Institute of TechnologyBeijing 100081China Beijing Key Laboratory of Embedded Real-time Information Processing Technology the Chongqing Institute of Meteorological Sciences Chongqing 401147China

The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor ***-based synthetic aperture radar(SAR)is an observation technique for high resolution imaging of *** ground-based SAR requires a long integration time to achieve a large synthetic aperture,and the echo signal will be seriously affected by temporal-spatial variant *** spatiotemporal freezing tropospheric models are *** cope with this,this paper models and analyses the impacts of temporal-spatial variant troposphere on ground-based SAR imaging of *** the background tropo-sphere,a temporal-spatial variant ray tracing method is proposed to trace the 4D(3D spatial+temporal)refractive index network provided by the numerical weather model,and calculate the error of the background *** the tropospheric turbulence,the Andrew power spectral model is used in conjunction with multiphase screen theory,and varying errors are obtained by tracking the changing position of the pierce point on the phase *** simulation,the impact of temporal-spatial variant tropospheric errors on image quality is analyzed,and the simulation results show that the X-band echo signal is seriously affected by the troposphere and the echo signal must be compensated.

关键词： near-Earth asteroids ground-based SAR troposphere ray tracing

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SAR doppler center frequency parameters estimation parallel optimization based on multi-core ARM NEON technology

SAR doppler center frequency parameters estimation parallel ...

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2017 International Conference on Radar Systems, Radar 2017

作者： Xing, Shiwen Xie, Yizhuang Chen, Liang Li, Bingyi Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781785615153

Obtaining Doppler center frequency parameters estimation (DCFPE) with low time consumption is a great challenge in synthetic aperture radar (SAR) imaging system. In order to get DCFPE in real time, this paper adopts three parallel acceleration implementation methods-SIMD parallelism, multi-issue parallelism and multi-core parallelism-according to the characteristics of DCFPE algorithm. To verify the efficiency of the proposed methods, the paper builds the ARM embedded Linux system on multi-core ARM Cortex-A9 platform and uses assembly programming language to implement DCFPE algorithm in a 16384*16384 64-bit SAR imaging process. The experiment shows that DCFPE can be accelerated by more than 50% on average with an acceptable accuracy of the result. © 2017 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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Moving object detection and tracking based on Zynq FPGA and ARM SoC

Moving object detection and tracking based on Zynq FPGA and ...

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IET International Radar Conference 2015

作者： Liu, Wenchao Chen, He Ma, Long Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781849199940

In this paper, an FPGA-based moving object detection and tracking system is introduced for image processing application. The algorithms presented include object detection based on dynamic background difference, kalman filter for object tracking. The target device for the implementation is a Xilinx Zynq-7000 FPGA. The use of ARM dual core processor, NEON vector coprocessor unit and coprocessing IP peripherals generated by vivado HLS aim to improve the data processing ability of the system. In the dynamic background, the system realized accurate detection and tracking of moving objects in real-time.

关键词： Field programmable gate arrays (FPGA)

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Implementation on FPGa for CORDIC-based computation of arcsine and arccosine

Implementation on FPGa for CORDIC-based computation of arcsi...

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IET International Radar Conference 2015

作者： Liu, Xiaoning Xie, Yizhuang Chen, He Li, Bingyi Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781849199940

This paper concentrates on the hardware implementation of CORDIC algorithm for computing inverse trigonometric functions like arcsine and arccosine. We improve the existing algorithm by changing the initial rotating vector of the iterations and modifying the judging condition of rotation direction. Due to the improvement, two iterations are saved and the drawback of the previous algorithm is corrected. In contrasting with the previous implementation, the improved algorithm consumes less hardware resources and its computing results are more accuracy.

关键词： Field programmable gate arrays (FPGA)

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Methods to improve system verification efficiency in FPGA-based spaceborne SAR image processing system

Methods to improve system verification efficiency in FPGA-ba...

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IET International Radar Conference 2015

作者： Yang, Zhu Long, Teng Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781849199940

With the rapid development of satellite-based signal processing technologies comes the widespread deployment of SAR image processing systems in spaceborne applications, many of which are implemented as FPGA-based systems thanks to the introduction of modern programmable devices with high capacity and complexity. However, as raw data of SAR satellites grow in size and bandwidth the effective implementation and especially the efficient system verification are emerging as the bottleneck in the development of FPGA-based SAR image processing systems. This paper proposes methods in the verification phase of FPGA-based SAR processing system development which on one hand increases the verification speed during simulations and on the other addresses the hardware/Matlab mismatch issue through comparison of floating point numbers on grounds of error analysis from a mathematical approach. Actual development process indicate that the proposed methods guarantee quick design convergence, and test results on real hardware confirm that the SAR image processing system offers acceptable quality of image output.

关键词： Field programmable gate arrays (FPGA)

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Change detection in optical remote sensing images based on watershed segmentation

Change detection in optical remote sensing images based on w...

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IET International Radar Conference 2015

作者： Mai, Zhihong Shi, Hao Xie, Yizhuang Ma, Long Bejing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781849199940

A novel approach is presented for change detection of very high resolution (VHR) remote sensing images in this paper, which is achieved by an improved watershed segmentation and mutual correlation. Specifically, the input multitemporal images are watershed segmented separately in the first stage. And then fuse the segmentation regions of two segmented images, which is also a combination of object outlines in other words. Finally, the change mask can be acquired by the mutual correlation method. Experimental results show the superiority of the proposed method over the Markov random filed (MRF) method to the VHR urban optical remote sensing images.

关键词： Change detection

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Word length optimization for sliding spotlight SAR imaging

Word length optimization for sliding spotlight SAR imaging

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2017 International Conference on Radar Systems, Radar 2017

作者： Wei, Chunpeng Yang, Chen Xie, Yizhuang Chen, He Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781785615153

With the development of the high-resolution synthetic aperture radar (SAR) technology, the spaceborne SAR has become a hot research topic. However there is a contradiction between hardware resource occupation and imaging accuracy in hardware implementation. realizing the algorithm with the fixed-point instead of the floating-point is an effective solution for this problem. In this paper we propose a method in which the fixed-point is used for all FFT operations rather than entire operations of algorithm. We simulate the point target and area target. We evaluate the image quality to obtain the relationship between the word length and SAR imaging assessment indexes. The results show that the 13-bit word length can make a good balance between hardware resource occupation and sliding spotlight SAR imaging accuracy in the case of 16384×8192 imaging granularity and 1m resolution. © 2017 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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