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SAR target recognition combining class information and classification hyperplane

SAR target recognition combining class information and class...

引用

IET International Radar Conference (IET IRC 2020)

作者： D. Yao Z. Liu F. Li Y. Li School of Information and Electronics Beijing Institute of Technology Radar Research Laboratory Beijing 100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing 100081 China

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.

关键词： support vector machines image recognition pattern classification radar target recognition feature extraction image classification radar imaging synthetic aperture radar

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Novel acceleration compensation method for highly squint mode SAR with curve trajectory

Novel acceleration compensation method for highly squint mod...

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IET International Radar Conference 2018, IRC 2018

作者： Zhou, Zhichao Ding, Zegang Zeng, Tao Li, Gen Li, Linghao School of Information and Electronics Beijing Institute Technology Beijing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China

Due to the influence of air currents and the control of the platform's own power system, acceleration is often present in the motion platform equipped with synthetic aperture radar (SAR) system, which causes the actual trajectory of the platform to be curved. When the acceleration is large or the azimuth accumulation time is long, a large envelope error or phase error will be caused. This problem will be more obvious in highly squint mode SAR. On the other hand, the acceleration may also cause the situation where the absolute value of the Doppler frequency rate is extremely small, resulting in the azimuthal time-bandwidth product that is too small to satisfy the requirements of the stationary phase principle. To solve the above problems, a novel acceleration compensation method based on inertial navigation information is proposed in this article. By integrating the acceleration and velocity information provided by the inertial navigation system, the position information of maneuvering platform is obtained. Then the actual trajectory of the platform is constructed. On this basis, the envelope and phase errors caused by the acceleration are estimated. The results of real data processing verify the correctness of the analysis and the effectiveness of the proposed method. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Acceleration

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A robust ragged cloud detection algorithm for remote sensing image

A robust ragged cloud detection algorithm for remote sensing...

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IET International Radar Conference 2018, IRC 2018

作者： Zhen, Li Baojun, Zhao Linbo, Tang Wenzheng, Wang Boya, Zhao School of Information and Electronic Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

Cloud detection plays a significant role in remote sensing (RS) image processing. Numbers of cloud detection algorithms have been developed in the literature. However, they suffer the weakness of omitting thin and small cloud, and poor ability of differentiating the cloud from confusing ground region (e.g. artificial building). In this study, a robust ragged cloud detection algorithm for RS image is proposed. First, the simple linear iterative clustering method is applied to segment ragged cloud. Then, the improved Qtsu's method is introduced to remove the redundant superpixel. Finally, the Natural Scene Statistic is designed to classify the cloud region. Finally, original image will be classified into thick cloud, thin cloud and non-cloud. Experimental results indicate that the proposed model outperforms the state-of-the-art methods for cloud detection. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Iterative methods

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

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

ISBN: (纸本)9781728123455

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. © 2019 IEEE.

关键词： Antennas

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DDMA-MIMO Radar Maximum Unambiguous Velocity Extension Based on Global Optimization Phase Modulation

DDMA-MIMO Radar Maximum Unambiguous Velocity Extension Based...

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IEEE International Conference on Radar

作者： Hongfei Lian Fugang Lu Qiao Chen Jiamin Long Xueyao Hu Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China No. 203 Research Institute of China Ordnance Industries Xi'an China Beijing Science and Technology Ruixing Electronic Technology Co. Ltd 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)9781665468893

Doppler division multiple access (DDMA) waveform shows great orthogonality for multiple-input multiple-output (MIMO) radar. However, it leads to a serious velocity ambiguous problem and hinders its application in automotive radar. In this work, a maximum unambiguous velocity extension approach is developed for DDMA MIMO radar by using a global ergodic optimization phase modulation during transmission. To be specific, we take the cumulative sum of the peak amplitude difference of global as the optimization cost function to obtain modulation codes. Furthermore, a matched filter phase demodulation carried out at the receiver to determine the results of angle measurement and velocity expansion. Finally, the simulation analysis and real-data experiments demonstrate our approach effectively improves velocity ambiguity resolving capabilities of DDMA waveform and suitable for massive MIMO array in nowadays automotive radar.

关键词： Matched filters Codes Phase modulation MIMO radar Radar detection Radar Doppler radar

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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...

引用

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

作者： Li, Yong Chen, Jing Ke, Meng Li, Linghao DIng, Zegang Wang, Yan 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: (纸本)9781728123455

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 ability 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. © 2019 IEEE.

关键词： Synthetic aperture radar

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Remote Sensing Image Classification Based on Markov Random Field

Remote Sensing Image Classification Based on Markov Random F...

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

作者： Zhang, Tong Zhuang, Yin Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China School of Electronic Engineering and Computer Science Peking University Beijing China

ISBN: (纸本)9781728123455

With the continuous development of optical remote sensing technology, the segmentation of high resolution remote sensing images has become a hot research field. The high resolution and complex remote sensing images make the general natural image segmentation become a challenge task. Here, Markov random field (MRF) can well combine the spatial information of remote sensing image with the domain information between pixels for image segmentation, which is currently a hot research direction. In this paper, the wavelet and MRF are combined to achieve multi-scale analysis and produce more accurate segmentation results, the extensive experiments demonstrated that proposed method is more suitable for remote sensing image segmentation, and it provides a good boundary local mapping results and is robust with image non-stationary signal. In addition, in view of the disadvantage of fixed potential function parameters of traditional MRF, we put forward the method of variable weight. On this basis, Kullback-Leibler (KL) divergence is proposed to calculate the similarity between the segmented regions to further optimize the segmentation results. © 2019 IEEE.

关键词： Image segmentation

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Research on Infrared and Vsisible Image Fusion System

Research on Infrared and Vsisible Image Fusion System

引用

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

作者： He, Xinxin Tang, Linbo Wu, Chen 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)9781728123455

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. © 2019 IEEE.

关键词： Image fusion

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

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

引用

IET International Radar Conference (IET IRC 2020)

作者： H. Dong C. Zheng W. Tian School of Information and Electronics Beijing Institute of Technology Radar Research Lab Beijing 100081 China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing 100081 China

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.

关键词： parallel architectures field programmable gate arrays radar signal processing digital signal processing chips graphics processing units radar computing multi-threading

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The Reconfigurable Pipelined Variable-point FFT Processor Design

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

引用

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

作者： Wang, Jiale Xie, Yizhuang Li, Bingyi Yang, Chen Hu, Shankang 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)9781728123455

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-2k, By analyzing and comparing the radix 2k algorithm, the radix-23 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-22/radix-2. This paper realizes an architecture of the single channel delay feedback variable-point, high precision FFT processor. © 2019 IEEE.

关键词： Fast Fourier transforms

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