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Space Target Super-resolution Based on Low-complex Convolutional Networks

Space Target Super-resolution Based on Low-complex Convoluti...

引用

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

作者： Tingting Cui Linbo Tang Jinghong Nan Zhenzhen Li Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

The images super-resolution is a key technique for space target, which has important research significance and application value. However, the traditional super-resolution algorithms always fail to achieve a good reconstruction effect due to limited information and inaccurate manual design models. Moreover, deep learning algorithms mainly focus on improving reconstruction with the price of high complexity. To address the above issues, we propose an improved space target super-resolution based on low-complex convolutional neural networks. Specifically, we construct a three-layer convolutional neural network by changing network layers and convolution kernels, which reduces the number of parameters and improves the extraction characteristics and reconstruction. Meanwhile, we establish a complete training data set, which solves the problem that the space target images are difficult to obtain. The experimental results demonstrate that the algorithm proposed can achieve the space target super-resolution. Compared with other algorithms, our algorithm obtains better subjective visual effects and objective evaluation indicators.

关键词： super-resolution deep learning convolutional neural networks

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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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Robust knowledge-aided sparse recovery STAP method for non-homogeneity clutter suppression

Robust knowledge-aided sparse recovery STAP method for non-h...

引用

IET International Radar Conference 2018, IRC 2018

作者： Peng, Hao Sun, Yuze Yang, Xiaopeng Yang, Jian Beijing China Department of Electronic Engineering Tsinghua University Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology School of Information and Electronic Beijing Institute of Technology Beijing China

Conventional space-time adaptive processing (STAP) methods would suffer severely performance loss in the complex clutter environment of an airborne-phased array radar, especially when the estimated clutter covariance matrix (CCM) is corrupted by the interference targets (outliers). In order to improve the clutter suppression in a practical complex clutter, a robust knowledge-aided sparse recovery STAP method for non-homogeneity clutter suppression is proposed. In the proposed method, the spectral profiles of the clutter and outliers are firstly estimated by sparse recovery processing. Then based on the system prior parameters, the clutter mask is constructed to select the space-time steering vectors corresponding to the clutter components. Afterwards the clutter suppression is achieved based on the clutter subspace obtained from the selected space-time steering vectors. Since the clutter and outlier profiles are effectively estimated and distinguished by the knowledge-aided sparse recovery processing, robust clutter subspace estimation can be achieved for clutter suppression. Through the simulated and actual airborne-phased array radar data, it is verified that the proposed method can effectively improve the STAP performance in a non-homogeneous environment. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Space time adaptive processing

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Radar data simulation using deep generative networks

Radar data simulation using deep generative networks

引用

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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SAR Parameter Estimation Method for Rectangle Plane Based on information Geometry

SAR Parameter Estimation Method for Rectangle Plane Based on...

引用

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

作者： Yuhan Wen Xinliang Chen Yangkai Wei Yujie Fan Tao Zeng Zegang Ding Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

After establishing scattering models, the traditional synthetic aperture radar (SAR) parameter estimation methods usually utilize vanilla gradients to estimate target parameters from SAR echoes or images. However, the vanilla gradients will lead to lower iteration efficiency. Hence, in this paper, to take the rectangle plane as an example, we propose a SAR parameter estimation method based on the information geometry (SPEM-IG) to solve the above problem. The SPEM-IG adopts the natural gradient to estimate the parameters based on the information geometry optimization algorithm. The central objective of SPEM-IG is to project the least square function into probability distribution space and find the optimal solution in the new parameter space. In order to reduce the computational complexity caused by the multi-peak feature of least squares function, SPEM-IG utilizes the range of parameters rather than its exact value in calculating the value of least squares function, and takes the optimal solution in this range as the result of the current iteration process. By considering the geometric structure of manifolds, SPEM-IG calculates the optimal gradient direction called natural gradient to obtain faster convergence rate. The experimental results show that the SPEM-IG is effective for estimating target parameters. Besides, SPEM-IG has good performance even at low signal-to-noise ratios of SAR images.

关键词： parametric scattering model information geometry natural gradient

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Research on Infrared And Vsisible Image Fusion System

Research on Infrared And Vsisible Image Fusion System

引用

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

作者： Xinxin He Linbo Tang Chen Wu Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

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.

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High-efficiency scene classification based on deep compressed-domain feature

High-efficiency scene classification based on deep compresse...

引用

IET International Radar Conference 2018, IRC 2018

作者： Li, Cheng Zhao, Baojun Zhao, Boya Wang, Wenzheng Duan, Chenhui 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

Remote sensing image (RSI) scene classification has become a more and more fundamental issue in satellite and UAV time-sensitive applications. However, as the volume and velocity of RSIs are undergoing an explosive growth, traditional effective technologies claim a huge amount of computing resources, on a scale that already goes beyond in-orbit processing capacity. Here, we attempt to design a deep feature representation framework based on onboard compressed data to solve the aforementioned problem. Firstly, we extract header and body information in raw JPEG2000 codestream for representing geometrical and geospatial property of RSIs. Moreover, a novel compressed-domain convolutional neural network (CNN) is proposed to obtain high-level representation for effective classification. Extensive experiments demonstrate that, in comparison with the existing relevant state-of-the-art approaches, the proposed method achieves high classification accuracy with faster computation and lower consumption. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Orbits

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Spaceborne synthetic aperture radar imaging mapping methodology based on FPGA-DSP hybrid heterogeneous architecture

Spaceborne synthetic aperture radar imaging mapping methodol...

引用

IET International Radar Conference 2018, IRC 2018

作者： Yu, Wenyue Xie, Yizhuang Li, Bingyi Chen, He Liu, Xiaoning Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China DFH Satellite Co. Ltd. Beijing100081 China

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data bring challenges for high-speed transmission and real-time processing. The general platform with GPU, CPU or digital signal processor (DSP) cannot meet the requirement for short delay and low power. Therefore, a field-programmable gate array-digital signal processor (FPGA-DSP) SAR imaging accelerate platform has become a solution for processing performance with a lower latency and power. In this study, an effective mapping strategy is adopted to the FPGA-DSP hybrid heterogeneous architecture to accelerate the processing performance according to the analysis of Chirp Scaling SAR imaging algorithms. As a proof of concept, a FPGA-DSP hybrid heterogeneous accelerating platform is designed and realised. The platform requires 12 s to focus a stripmap SAR raw data with a granularity of 16,384 × 16,384. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Digital signal processors

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