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Optical Remote Sensing Image Waters Extraction technology Based on Deep Learning Context-Unet

Optical Remote Sensing Image Waters Extraction Technology Ba...

引用

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

作者： Yan, Ruoda Dong, Shan Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China Engineering Center of Digital Audio and Video Communication University of China Beijing100024 China

ISBN: (纸本)9781728123455

The optical remote sensing images are used to sea-land segmentation which is a difficult task. Due to general deep learning based methods required a large number of refined annotation, however, a large scale optical remote sensing images annotation is very expensive. Therefore, the Context-Unet is proposed to produce accurate sea-land segmentation results by a few annotated training samples. In this paper, we apply the Context-Unet network to the watershed extraction. On the basis of this, we re-compile the loss function to improve the accuracy of watershed extraction. Example: Finally, the date collected from Google Earth service is used to train and test this paper proposed Context-Unet and state-o-the-art methods. The experiments proved that the proposed method outperforms than other methods, and it can achieve 98% precision and 97% recall ratios. © 2019 IEEE.

关键词： Object detection

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Implementation and optimisation of pulse compression algorithm on open CL-based FPGA

Implementation and optimisation of pulse compression algorit...

引用

IET International Radar Conference 2018, IRC 2018

作者： Feng, Yingxu Hu, Shanqing Li, Xingming Yu, Jiacheng Beijing Key Laboratory of Embedded Real-time Information Processing Technology School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Science and Technology Leike Electronic Information Technology Beijing10081 China

As Moore's law meets bottlenecks, the demand for heterogeneous parallel processing systems is increasing. Field-programmable gate arrays (FPGAs) are becoming more efficient acceleration devices due to their powerful processing performance, and the CPU + FPGA architecture under the OpenCL framework has become the trend of heterogeneous parallel processing systems. This study focuses on the optimisation of pulse compression algorithm in FPGA based on OpenCL, which plays an important role in modern radar signal processing systems. By using double cache for ping-pang storage of data between matched filter and inverse fast Fourier transform (IFFT), an optimised processing method is proposed by using a pipeline and verify the method by using Arria 10 GX1150 FPGA with two groups of 2 GB DDR3;the results show that the proposed method can achieve 2.89× performance improvement over the conventional implementation. © This is an open access article published by the IET under the Creative Commons Attribution License (http://***/licenses/by/3.0/)

关键词： Parallel processing systems

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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

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

作者： Nan, Jinghong Zhao, Baojun Cui, Tingting Xie, Yongfeng 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 Beijing Institute of Aerospace Systems Engineering Beijing China

ISBN: (纸本)9781728123455

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. © 2019 IEEE.

关键词： Image enhancement

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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

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

作者： Wang, Ce Hu, Shanqing Li, Xingming Chen, Yingying Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology China Beijing Racobit Electronic Information Technology Co. Ltd China

ISBN: (纸本)9781728123455

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. © 2019 IEEE.

关键词： Field programmable gate arrays (FPGA)

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realization of fixed-point SAR imaging based on embedded GPU

Realization of fixed-point SAR imaging based on embedded GPU

引用

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

作者： Li, Huixing Gao, Zixin Li, Bingyi Xie, Yi Zhuang 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 Beijing Institute of Radio Measurement Beijing China

ISBN: (纸本)9781728123455

Aiming at the problem of insufficient memory in the real-time processing of SAR imaging on embedded TX2, this paper studies a design optimization scheme of fixed-point imaging algorithm on TX2. In order to ensure the accuracy, this paper only performs fixed-point processing on the FFT. According to the characteristics of the algorithm, the memory multiplexing method is adopted to effectively reduce the occupation of the work area buffer. A large number of registers are used to improve computing performance. The results show that the fixed-point FFT processing scheme can achieve a hundred times faster than the Intel Xeon CPU, and the memory footprint is less. © 2019 IEEE.

关键词： Fast Fourier transforms

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FPGA-based fault injection design for 16K-point FFT processor

FPGA-based fault injection design for 16K-point FFT processo...

引用

IET International Radar Conference 2018, IRC 2018

作者： Mao, Chuang-An Xie, Yu Wei, Xin Xie, Yi-Zhuang Chen, He Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China

There are a number of satellites working in the harsh space environment. The charged particles in space may strike the electron devices causing the undesired influences, such as soft errors in memory devices or permanent damage in hardware circuits. Aiming at reliability evaluation of very-large-scale integration circuits implemented in SRAM-based field programmable gate arrays, a fault injection platform is constructed based on the soft error mitigation controller in this study. The authors adopt a 16K-point fast Fourier transformation processor as the design under test (DUT) and inject errors into different positions. The effectiveness of this platform is varied by comparing the results of DUT with Golden data. Compared with the traditional reliability testing techniques, the fault injection method proposed in this study has the advantages of low cost, short test period and low resource consumption. Hence, the proposed fault injection design is suitable for circuits consuming huge resources and large number of repeating tests. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Static random access storage

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Parallel processing of sliding spotlight mode SAR imaging based on GPU

Parallel processing of sliding spotlight mode SAR imaging ba...

引用

IET International Radar Conference 2018, IRC 2018

作者： Gao, Zixin Wei, Chunpeng Yang, Chen Xie, Yizhuang Chen, He Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China

Sliding spotlight synthetic aperture radar (SAR) is a hot imaging mode in space-borne SAR. It can acquire high-resolution and large azimuth scene size simultaneously. The main challenges for sliding spotlight SAR processing in real time are the huge volume of raw data and complex imaging algorithm. The rapid development of the graphics processing units (GPUs) provides a new computing platform for high-performance SAR processing. This work presents a parallel processing of sliding spotlight SAR imaging algorithm on GPU via compute unified device architecture and tests the speedup of each module of the algorithm on the K20c GPU platform from the aspect of a small granularity and a large granularity of point target images. Compared with traditional CPU-based SAR imaging technology, the proposed GPU-based sliding spotlight SAR imaging obtains a speedup of 186.80 when processing data with a granularity of 16,384 × 8192 and gets a speedup of 49.72 when processing data with a granularity of 65,536 × 32,768, thereby greatly improving the real-time imaging processing. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Graphics processing unit

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Research on the method of fast inverse realisation of Vandermonde matrix based on FPGA

Research on the method of fast inverse realisation of Vander...

引用

IET International Radar Conference 2018, IRC 2018

作者： Chen, Lei Chen, Liang Li, Bing Y. Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China

With the rapid development of science and technology, the operation and calculation in synthetic aperture radar (SAR) imaging systems require high throughput, and the system has high requirement for real-time performance. At the same time, in the SAR imaging technology, many Vandermonde matrix inversion operations are used in places where the weight coefficients are calculated. Especially when multi-channel inverse filtering is performed, the use of the Vandermonde matrix inversion operation is a crucial step. In this study, the authors worked hard to find a high speed and accurate Vandermonde matrix inversion algorithm for complex SAR imaging systems. Considering the field-programmable gate array (FPGA) can be parallel computing and its computing speed is high, the authors chose FPGA to achieve a large number of Vandermonde matrix inversion calculation, and it can meet the requirements of high speed and real time. So, first the realisation method of the fast inversion of the Vandermonde matrix based on Lagrange interpolation polynomial is discussed in this study, which includes pre-processing module, u matrix calculation module, v matrix calculation module, π′ vector calculation module and post-processing module. Then, the simulation results of the design are compared and analysed, which proved the correctness and feasibility of the rapid inversion method of Vandermonde matrix. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Imaging systems

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Multi-scale object detection by bottom-up feature pyramid network

Multi-scale object detection by bottom-up feature pyramid ne...

引用

IET International Radar Conference 2018, IRC 2018

作者： Boya, Zhao Baojun, Zhao Linbo, Tang Chen, Wu Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China

The deep neural networks has been developed fast and shown great successes in many significant fields, such as smart surveillance, self-driving and face recognition. The detection of the object with multi-scale and multi-aspect-ratio is still the key problem. In this study, the authors propose a bottom-up feature pyramid network, coordinating with multi-scale feature representation and multi-aspect-ratio anchor generation. Firstly, the multi-scale feature representation is formed by a set of fully convolutional layers which is catenated after the backbone network. Secondly, in order to link the multi-scale feature, the deconvolutional layer is involving after each multi-scale feature map. Thirdly, to tackle the problem of adopting object with different aspect ratios, the anchors on each multi-scale feature map are generated by six shapes. The proposed method is evaluated on PASCAL visual object detection dataset and reach the accuracy of 80.5%. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Aspect ratio

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Radar data simulation using deep generative networks

Radar data simulation using deep generative networks

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IET International Radar Conference 2018, IRC 2018

作者： Song, Yiheng Wang, Yanhua Li, Yang Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China

Due to the high cost of real experiments, radar data simulation plays an important role in radar applications. However, the accuracy and the calculation speed of existing simulation methods is limited by the model error and the heavy calculation of electromagnetic simulation. Here, a radar data simulation method based on deep generative network (DGN) is proposed. DGN is generative model involving deep network as the representation tool, in which the model is trained with labelled data. When the training phase is finished, the generative model can generate data samples which are similar to the real samples. The performance of the DGN is evaluated on the ground-based radar dataset, and the results show that the distribution of the generated radar data is similar to the training radar data. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Electromagnetic simulation

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