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共 577 条记录，以下是201-210 订阅

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Preliminary Result of MIMO SAR Tomography via 3D FFBP

Preliminary Result of MIMO SAR Tomography via 3D FFBP

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Linghao Li Yan Wang Zegang Ding Minkun Liu Tao Zeng Teng Long Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Linear array multiple-input multiple-output synthetic aperture radar (LA-MIMO SAR) tomography can provide 3-D radar images without layover and geometric distortion effects. However, suffering from the channel and motion error, and large computation, the real LA-MIMO-SAR data is difficult to be well focused quickly. Therefore, the 3-D imaging results of real LA-MIMO-SAR data are rarely shown in existing literature. In this paper, real LA-MIMO-SAR data imaging processing method based on 3-D fast factorized Backprojection is proposed to well focus the echoes with channel and motion errors, and large size of data. Then, our experiments of LA-MIMO-SAR 3-D imaging are demonstrated. The LA-MIMO radar is installed to a special tower crane and works in downward-looking and forward-looking geometry. Some 3-D imaging results are demonstrated to verify the downward-looking and forward-looking LA-MIMO-SAR modes and the processing method.

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Correlation tracking via robust region proposals

Correlation tracking via robust region proposals

引用

IET International Radar Conference 2018, IRC 2018

作者： Han, Yuqi Nan, Jinghong Zhang, Zengshuo Wang, Jingjing Zhao, Baojun School of Information and Electronics Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

Recently, correlation filter-based trackers have received extensive researching interest because of their simplicity and superior running speed. However, such trackers perform poorly when the target undergoes occlusion, viewpoint change, or other challenging attributes due to pre-defined sampling strategy. To tackle these issues, the authors propose an adaptive region proposal strategy to facilitate object tracking. To be more specific, a novel tracking monitoring indicator is advocated to forecast tracking failure. Afterwards, detection and scale proposals were incorporated, respectively, to recover from model drift as well as handle aspect ratio variation. The algorithm was tested on several challenging video sequences, which demonstrates that the proposed algorithm outperforms other state-of-the-art trackers. © 2019 Institution of Engineering and technology. All rights reserved.

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Spatial-Temporal Segmentation-based Tracking

Spatial-Temporal Segmentation-based Tracking

引用

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

作者： Han, Yuqi Xiao, Zhongyang Tang, Linbo Beijing Key Laboratory of Embedded Real-time Information Processing Beijing China State Key Laboratory of Automotive Safety and Energy Beijing China

ISBN: (纸本)9781728123455

Visual tracking, a fundamental task in computer vision, has been criticized less well-posed since reliable target information only given at first frame. In this case, most of the existing template-matching-based trackers fail to locate the target when non-rigid deformations or variations occur. To address these issues, we propose a principled way to take advantage of the superpixel labeling and discriminative tracking algorithms. For each frame, a correlation tracker is first adopted to provide the coarse target location. Afterwards, a collaborative segmentation approach is advocated to segment the surrounding region of the target into superpixels. Target appearance and motion trajectory are considered as spatial and temporal constrains and incorporated into superpixel labeling module. The fine-segmentation result, in turn, provides a more accurate target status for template updating. The effectiveness of the proposed algorithm is validated through experimental comparison on widely-used tracking benchmark datasets. © 2019 IEEE.

关键词： Superpixels

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Aircraft detection in Remote Sensing image for Space-borne platform

Aircraft detection in Remote Sensing image for Space-borne p...

引用

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

作者： Tang, Wei Jun, Baozhao Tang, Linbo Pan, Yu Jin, Dongling Quan, Zhengpiao 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

ISBN: (纸本)9781728123455

Aircraft detection in optical remote sensing image is an important research direction in the field of remote sensing. The existing detection methods are difficult to achieve satisfactory results. Traditional detection methods are low robustness, due to manual feature modeling are difficult and subject to background interference;The deep learning target detection method, which improves the detection performance at the cost of complexity improvement, cannot be widely used in space-borne platforms limited resources. In view of the above problems, this paper proposes an aircraft target deep learning detection method of lightweight and multi-scale features. On the basis of the multi-scale target detection framework (SSD), the method firstly uses the dense connection structure and the double convolution channels to form the basic backbone networks with feature reuse and high computational efficiency. To improve the detection performance of the small aircraft target, the basis backbone network connects a residual module and deconvolution to compose the multi-scale feature fusion detection module. Compared with the current classical deep learning object detection methods, the experimental results show that the proposed method has the advantages of maintaining low computational complexity and achieving high detection accuracy. © 2019 IEEE.

关键词： Aircraft detection

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Fusion-based spectral matching method for hyperspectral target detection

Fusion-based spectral matching method for hyperspectral targ...

引用

IET International Radar Conference 2018, IRC 2018

作者： Wenzheng, Wang Baojun, Zhao Linbo, Tang Shichao, Zhou Fan, Feng School of Information and Electronic Beijing Institute of Technology China Beijing Key Laboratory of Embedded Real-time Information Processing Technology China

Target detection using hyperspectral images is one of the most important applications in the field of both civilian and military. Some spectral similarity metric methods have been used in those applications, i.e. spectral angle mapper and spectral gradient angle and so on. However, those methods only consider the similarity between two spectral in one aspect, and many information hidden in the spectrum is ignored. Then, here, the authors propose a new fusion-based spectral-matching method for hyperspectral target-detection task. The proposed Euclidean-angle matching method combines the magnitude and the shape difference together to determine the similarity between the test and target spectra samples. Authors' results indicate that the proposed fusion-based method exhibits a better performance over the other spectral-matching methods. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Military applications

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SAR Image Scattering Center Estimation via Atomic Norm Minimization 6

SAR Image Scattering Center Estimation via Atomic Norm Minim...

引用

6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Xi, Ying Liu, Haibo Wang, Yanhua Li, Yang Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

ISBN: (纸本)9781728129129

Scatter center matching is one of the choke points of radar automatic target recognition (RATR) based on Synthetic Aperture Radar (SAR). Accuracy of scattering center extraction is an important factor affecting target recognition performance. This paper proposes a SAR images scattering center estimation method based on atomic norm minimization (ANM) model. This method models the scattering center estimation problem as a two-dimensional line spectrum estimation problem, then the estimation is performed in a continuous domain via ANM. The experimental results indicate the superiorities of the proposed method in terms of accuracy and robustness. © 2019 IEEE.

关键词： Synthetic aperture radar

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Fast and robust adaptive beamforming method based on complex-valued RBF neural network

Fast and robust adaptive beamforming method based on complex...

引用

IET International Radar Conference 2018, IRC 2018

作者： Li, Yuqing Yang, Xiaopeng Liu, Feifeng Beijing Key Laboratory of Embedded Real-time Information Processing Technology School of Information and Electronics Beijing Institute of Technology Beijing100081 China

The adaptive beamforming is one of the key techniques for array signal processing. However, the matrix inversion operation in the existing methods will cost a large amount of computational complexity, which results in poor real-time processing ability. In order to reduce the amount of computational cost, a fast and robust adaptive beamforming method based on complex-valued radial basis function (CRBF) neural network is proposed. In the proposed method, the CRBF neural network is established, thus the direct matrix inversion is avoided by the nonlinear mapping processing from the array covariance matrix to the adaptive weight vector, and therefore the calculation speed of adaptive weight vectors is increased. Based on the simulation results, the proposed method is verified that the speed of adaptive beamforming is increased compared with sample matrix inversion (SMI) algorithm method and an improved performance is achieved compared with that of conventional real-valued RBF neural network beamformer. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Beamforming

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Three-dimensional optimal focusing imaging algorithm for wall-penetrating radar

Three-dimensional optimal focusing imaging algorithm for wal...

引用

IET International Radar Conference 2018, IRC 2018

作者： Li, Yinchuan Zhao, Yikun Xiang, Yin Ding, Zegang Liu, Haibo Liu, Quanhua Beijing Key Laboratory of Embedded Real-time Information Processing Technology School of Information and Electronics Beijing Institute of Technology Beijing100081 China

Wall-penetrating radar (WPR) is the device to image very small objects buried inside the wall. The small objects usually a few millimetres, whereas the bandwidth of WPR limits its resolution up to several centimetres. As a result, the target imaging result of the traditional method is 'defocused' in the range direction. To solve this problem, a near-field three-dimensional imaging algorithm based on matching filtering with multiple reference signals and selection processing is proposed. Instead of obtaining a focused image via coherent superposition processing, a focused image is determined by selecting an image from a plurality imaging results of different reference depths according to the minimum entropy criterion. The proposed algorithm is validated by imaging the computer simulation technology simulation data and the measured data. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Radar imaging

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

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

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

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.

关键词： feature extraction synthetic aperture radar support vector machines radar imaging image recognition object detection image classification

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Smart noise jamming suppression method based on fast fractional filtering

Smart noise jamming suppression method based on fast fractio...

引用

IET International Radar Conference 2018, IRC 2018

作者： Han, Bowen Yang, Xiaopeng Wu, Xuchen Li, Shuai Beijing Key Laboratory of Embedded Real-time Information Processing Technology School of Information and Electronics Beijing Institute of Technology Beijing100081 China

Smart noise jamming based on digital radio frequency memory (DRFM) has both oppressive jamming effect and deceptive jamming effect, and it is difficult to be effectively suppressed by traditional anti-jamming methods. In order to solve this problem, an anti-jamming method for linear frequency modulation (LFM) pulse compression radar system is proposed. The proposed method is combined with fractional Fourier transform (FrFT) and fractional domain filtering strategy. Here, first, the FrFT transform is performed on the received signal, and the optimal transform angle is calculated by calculating the fractional fourth-order origin moment. Then, the narrow-band filter is performed in the fractional domain to extract the target signal and suppress the jamming signal. Finally, fractional Fourier inverse transform is done to restore the target signal. The simulation results show that the method not only can effectively suppress smart noise jamming but also can accurately detect the position of the target. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Inverse problems

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