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Fast processing Techniques for Ground-Based Differential Interferometric Radar Based on embedded GPU

Fast Processing Techniques for Ground-Based Differential Int...

引用

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

作者： Jingshuang Qi Jian Wang Xiaoxiao Li Longyue Wang Yunkai Deng Weiming Tian Radar Technology Research Institute Bejing Institute of Technology Beijing China Beijing Building Research Institute Corporation Limited of CSCEC Beijing China Beijing Key Laboratory of Embedded Realtime Information Processing Technology Radar Technology Beijing China Chongqing Innovation Center Beijing Institute of Technology Chongqing China Advanced Technology Research Institute Beijing Institute of Technology Jinan China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

For ground-based differential interferometric radar systems, aiming at the problems of low operation-speed performance, a rapid processing technology was studied based on embedded GPU. To achieve effective processing of high-speed data streams, an architecture design based on message queues is adopted in this paper, enabling parallel data transmission and processing. Message queue, as an efficient middleware technology, not only ensure reliable data transmission but also enable decoupling of data reception and processing through an asynchronous communication mechanism. This significantly enhances the system's throughput and response speed. To further optimize performance, condition variables are introduced to control the concurrency strategy in the message queue. When there is data to be processed in the message queue, the condition variable wakes up waiting threads to start processing messages; when there is no data to be processed, it suspends the threads. This mechanism ensures the maximization of system resource utilization. Parallel reduction techniques based on shared memory are adopted to achieve rapid selection of persistent scatterer. Shared memory reduces data access times, and the use of parallel reduction techniques is particularly effective when handling large-scale datasets. The results show that for 200 images with dimensions of 634 by 100 pixels, the method presented in this paper improves the processing speed by 16% compared to traditional methods, effectively enhancing the processing efficiency of ground-based differential interferometric radar systems.

关键词： Graphics processing units Radar Radar imaging Throughput Radar signal processing Resource management Reliability Streams Optimization Message systems

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Distorted SAR target recognition with virtual SVM and AP-HOG feature 5

Distorted SAR target recognition with virtual SVM and AP-HOG...

引用

IET International Radar Conference 2020, IET IRC 2020

作者： Yao, Di Liu, Zhenyuan Li, Feng Li, Yang Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China

ISBN: (纸本)9781839535635

Synthetic aperture radar (SAR) plays an indispensable role in national defence and civil fields due to its unique advantages. Although many methods have been proposed, the recognition to SAR images still faces many difficulties, especially to distorted images. This paper first improves the morphological methods attribute profiles (APs) which is widely employed with optical, and hyperspectral images in particular. We combine the APs method with histogram of oriented gradients (HOG) feature (called AP-HOG) to make it suitable for SAR images. Then, the SVM model is used to identify the labelled samples (i.e., Support Vectors) that are closest to the separating hyperplane with maximum margin. We generate different degrees of distorted images based on support vectors, and use the distorted image and the support vector as a new training set for retraining to improve the recognition effect of the distorted image. Finally, we perform experimental verification based on the MSTAR dataset, which proves the effectiveness of the proposed method. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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SAR target recognition using feature extraction of multi-scale monogenic components 5

SAR target recognition using feature extraction of multi-sca...

引用

IET International Radar Conference 2020, IET IRC 2020

作者： Li, Feng Yao, Weijun Li, Yang Radar Research Laboratory School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China

ISBN: (纸本)9781839535635

In this paper, we combine the monogenic signal with the histogram of oriented gradient (HOG) feature, and propose a new low-level feature: Monogenic-HOG (MG-HOG);then use the bag of words (BoW) model to construct the middle-level feature. Most of the existed features are directly extracted from grayscale synthetic aperture radar (SAR) images. As an extended representation of analytic signals in high-dimensional space, the monogenic signal has excellent characteristics such as rotation and scale invariance in the potential extraction process, and it is also valuable in the image field. However, in the past related work, it is mostly used directly as the feature representation of the image. After experimental validation on the moving and stationary target acquisition and recognition (MSTAR) data set, the proposed feature extraction method has better performance than a number of existed methods. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Feature extraction

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SAR target recognition combining class information and classification hyperplane 5

SAR target recognition combining class information and class...

引用

IET International Radar Conference 2020, IET IRC 2020

ISBN: (纸本)9781839535635

Automatic target recognition (ATR) in synthetic aperture radar (SAR) images plays an important role. An important step in SAR target recognition is to transform the raw data to a feature space with the property of within-class compactness and between-class separation. However, due to the problem of target aspect angle sensitivity in SAR images, the difference of some targets belonging to the same class in different poses is greater than the difference of targets belonging to different class in similar poses, which often causes misjudgement. To solve this problem, we first use the twin support vector machine (TWSVM) to obtain the classification hyperplane of each class. Then, based on the obtained hyperplane, the projection matrix is constructed by fusing the prior class information of the target. In this way, the sample can be close to the classification hyperplane of the same class and distant from the classification hyperplane of a different class. This algorithm can improve TWSVM's ability to classify SAR images. Experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) database. The results verify the effectiveness of the proposed algorithm. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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A Novel Image Recognition Method Based on CNN Algorithm 5th

A Novel Image Recognition Method Based on CNN Algorithm

引用

5th International Conference on Smart Computing and Communication, SmartCom 2020

作者： Guo, Yuwen Zhang, Xin Yang, Qi Guo, Hong 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 Beijing China

ISBN: (纸本)9783030747169

Handwritten digital image recognition is a special problem in digital recognition, which is much more difficult due to uncertainties such as writer and writing environment. But the accuracy of handwritten digital recognition is particularly important in some critical areas such as public security and finance. In this paper, we used machine learning and deep learning technology, to identify MNIST handwritten digital data sets. And the support vector machine and convolutional neural network were used to image recognition, among them, the support vector machine compares the accuracy of the identification of the two kernel functions. Convolutional neural networks are improved based on the classic LeNet-5 model. The Experiments result shown that the identification accuracy of Gaussian kernel function model and linear kernel function model is 94.03% and 90.47% for support vector machines, respectively. In contrast, Gaussian kernel function performs better, but the overall accuracy is low. The best performance is based on the classic convolutional neural network LeNet-5 improved model, the test set recognition rate can reach 99.05%. © 2021, Springer Nature Switzerland AG.

关键词： Support vector machines

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Research on parallel architecture design of radar real-time signal processing based on CPU-GPU heterogeneous platform 5

Research on parallel architecture design of radar real-time ...

引用

IET International Radar Conference 2020, IET IRC 2020

作者： Dong, Henan Zheng, Cheng Tian, Weiming Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China

ISBN: (纸本)9781839535635

in view of the central processing unit (CPU) platform processing performance limits on computationally intensive tasks, as well as the FPGA + DSP[1-3] platform of software and hardware of high coupling and difficult defects, using the graphics processor (GPU) powerful parallel computing power, the CPU and GPU pipeline technology, heterogeneous systems with multithreading, GPU more and more flow, such as strategy, puts forward the real-time signal processing system of the multiple perspectives analysis methods, make full use of the independence between modules and signal processing algorithm concurrency features within the *** experimental results show that, compared with the traditional MATLAB platform, the maximum acceleration ratio based on CPU-GPU heterogeneous platform can reach more than 20000, and the parallel architecture designed can fully meet the real-time requirements of radar signal processing. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Graphics processing unit

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Accurate slant range model in ground-based radar imaging of the lunar 5

Accurate slant range model in ground-based radar imaging of ...

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IET International Radar Conference 2020, IET IRC 2020

作者： Liu, Siyuan Ding, Zegang Li, Gen Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839535635

Ground-based radar imaging is an important approach for lunar observation. However, due to the long round-trip time delay and long integration time, the invalidation of "stop-and-go" hypothesis presents challenge to the radar imaging algorithms. In this paper, firstly, the accurate ephemeris of large-scale lunar surface is created based on the coordinate transformations. Secondly, considering the error of "stop-and-go" hypothesis, the accurate slant range model between the ground-based radar and lunar surface is presented. Finally, the simulation results are presented to verify the correctness of the ephemeris calculation, and demonstrate the slant range difference caused by the "stop-and-go" hypothesis. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Radar imaging

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FPGA-Based Implementation of Reconfigurable Floating-Point FIR Digital Filter 8th

FPGA-Based Implementation of Reconfigurable Floating-Point F...

引用

8th International Conference on Communications, Signal processing, and Systems, CSPS 2019

作者： Zhang, Ning Wei, Xin Li, Bingyi Chen, He 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 Beijing100081 China

ISBN: (纸本)9789811394089

As a critical digital signal processing method, finite impulse response (FIR) digital filter is widely used in radar signal processing, synthetic aperture radar (SAR) signal processing, etc. Furthermore, an efficient FIR hardware implementation contributes to the practical application of these processing. However, as a computation-intensive operation, the multiple high order FIR digital filter consumes a lot of hardware resources when implemented in commonly used chips such as field-programmable gate array (FPGA). In this paper, a reconfigurable FIR digital filter architecture is presented, which can perform different order FIR filtering operation without FPGA re-programming. In the experiment, the proposed FIR digital filter architecture was implemented and validated on the Xilinx Zedboard Evaluation Kit. The experimental results demonstrate that this design has a low consumption of hardware resources and can achieve real-time processing performance for digital signal processing in the practical applications. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Field programmable gate arrays (FPGA)

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Nonparametric resampling for high-squint synthetic aperture radar imaging 5

Nonparametric resampling for high-squint synthetic aperture ...

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IET International Radar Conference 2020, IET IRC 2020

作者： Li, Linghao Wang, Yan Ding, Zegang Min, Rui School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology China Beijing Institute of Technology of Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839535635

Synthetic aperture radar (SAR) image resampling is a key technology for SAR image geometric correction, interferometric and tomographic registration. In some geometry like the high-squint (HS) case, image spectrum will be distorted, folded and therefore, existing resampling methods will fail due to the resulting serious image degradation. To solve this problem, we propose a general nonparametric image resampling method for SAR. The main contribution is the new non-parametric method of morphologically generating image-domain interpolation kernel, which can be theoretically applied for an arbitrary SAR image focused either on slant range plane or ground plane. The presented approach is evaluated by showing resampled image quality improvement via the computer simulations. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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FPGA implementation of SAR bi-channel synthesis based on inverse filtering 5

FPGA implementation of SAR bi-channel synthesis based on inv...

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IET International Radar Conference 2020, IET IRC 2020

作者： Shao, Xin Shi, Hao Chen, Liang Zhang, Na 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 Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839535635

In a multi-channel synthetic aperture radar (MSAR) system, non-uniform azimuth sampling is an important factor affecting imaging. If it is not processed and then imaged directly, it will inevitably lead to deterioration of imaging performance. The channel synthesis algorithm based on inverse filtering is a method to solve this problem. However, in actual applications, it is necessary to perform specific optimization processing on the algorithm to meet real-time requirements. This paper designs a new architecture for efficient implementation of channel synthesis algorithms. The design makes full use of the parallel characteristics of FPGA to improve the speed of the algorithm. By optimizing the DDR read-write control logic, the data transfer rate is improved. Finally, the Modelsim software is used to obtain the simulation results. At 150 MHz, the processing speed could reach 461.6MSamples/s (64bit/sample). © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Data transfer

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