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检索条件"机构=Beijing Key Laboratory of Embedded Real-Time Information Processing Technology"

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Phaseerror analysis and estimation among different sub-channel sinmulti-channel space-borne SAR

Phaseerror analysis and estimation among different sub-chann...

引用

IET International Radar Conference 2015

作者： Wang, Z. Liao, X. Feng, D.B. Ding, Z.G. Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Radar Research Lab. School of Information and Electronics Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781785610387

SyntheticAperture Radar (SAR) has the ability to work inevery hour, under all weather conditions. The multichannel SAR well solved the dilemma between the swathcoverage and the azimuth resolution. However in reality, the phase equalization of each sub-channel is influencedby many unideal factors, which can degrade the imagequality. In this paper, firstly the main factors are summarized and their effects are calculated. Then the interferometric phasemethod is introduced to compensate the phase error. Finally we applied the following methods of error estimation and compensation in the channel uncertainty simulation and get a good imagining result.

关键词： Error compensation

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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

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

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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Experimentalvalidation for impacts of temporal-spatial variant ionosphere on GEO SAR using GNSS satellite signals

Experimentalvalidation for impacts of temporal-spatial varia...

引用

IET International Radar Conference 2015

作者： Dong, Xichao Hu, Cheng Zhang, Dandan Tian, Weiming Tian, Ye Long, Teng 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

ISBN: (纸本)9781849199940

Geosynchronous SAR (GEO SAR) is susceptible to ionosphere due to the ultra-long integration time and ultrawide coverage, resulting in image defocusing and image drift. This paper demonstrates a validation experiment of analysing ionospheric impacts on GEO SAR focusing. The validation experiment consists of data acquisition of the global navigation satellites system (GNSS) satellites signals (including GPS and Beidou IGSO satellites), equivalent pre-processing, GEO SAR signal modelling, image focusing and evaluating. The recorded data are equivalently transformed into the space and time frame of GEO SAR. Then the phase errors induced by ionosphere in GEO SAR can be generated from the equivalently preprocessed data and then incorporated into the GEO SAR signals. The following image focusing and the impacts analysis are accomplished. In cases of the current GEO SAR system configuration, the existence of ionosphere will induce image drifts but can be corrected through image registration techniques. In other aspects, the image can be well focused in range direction. But for the azimuthal focusing, the second and higher derivatives of TEC will result in defocusing and the thresholds of wellfocusing are dependent on the specific GEO SAR system configuration.

关键词： Synthetic aperture radar

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Parallel realization of SIFT feature abstraction based on GPU using Tegra K1

Parallel realization of SIFT feature abstraction based on GP...

引用

IET International Radar Conference 2015

作者： Jiang, Donglin Long, Jianzhi Yu, Wanwan Jin, Ye Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China High School Affiliated Renmin University of China Beijing China

ISBN: (纸本)9781849199940

The fast and steady feature extraction and key point matching are key factors to SAR (synthetic aperture radar) image automatic registration algorithm. The real-time processing of the algorithm in SAR is one of the challenges that need to be solved urgently. This paper aims at improving the efficiency of the description of key point in SIFT algorithm. We implemented the rapid calculation of the feature extraction section in SIFT (scale invariant feature transform) based on embedded NVIDIA GPU-Tegra K1 by fully taking the advantages of multi-cores of GPU in parallel computing, floating point calculation, memory management, etc. And the speed ratio of the accelerated calculation of the SIFT feature reaches 5.5.

关键词： Feature extraction

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

Novel acceleration compensation method for highly squint mod...

引用

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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Texture-based urban detection using contourlet coefficient on remote sensing imagery

Texture-based urban detection using contourlet coefficient o...

引用

IET International Radar Conference 2015

作者： Li, Cheng Pang, Zhaofeng Zhao, Baojun Wang, Shuigen 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

ISBN: (纸本)9781849199940

This paper presents an original urban detection on remote sensing images, which is based on efficient textural features extracted from contourlet transform domain. Since cities and towns are consisted of various objects, which have great differences in scale, directivity and texture characteristics, it is adaptive for contourlet transform to detecting urbans result from its discrete-domain multi-resolution and multi-direction expansion using nonseparable filter banks. Therefore, construction of contourlet coefficients can capture the intrinsic geometrical structure that is the key in visual information. On the other hand, we employ robust texture features in contourlet domain for recognizing urban regions from other land type by LS-SVM classifier. The performance of the proposed approach was validated by experiments carried on a data set of large images consisting of heavily negative samples.

关键词： Contourlet transform

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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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Coherent parameters estimation method based on MUSIC and KF in Wideband DCAR

Coherent parameters estimation method based on MUSIC and KF ...

引用

IET International Radar Conference 2015

作者： Zhang, H.G. Lei, Z.J. Song, Y.Y. 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

ISBN: (纸本)9781785610387

Wideband distributed coherent aperture radar has become the most significant direction in next generation radar. Its high range resolution due to wideband and high angle resolution because of distributed aperture can accurately estimate the target's range and angle. In result, tracking and identification can be employed. However, single radar cannot detect the long-range target because of its relatively low SNR. Therefore, precisely estimating the coherent parameters under low SNR in order to achieve the coherent synthesize is the key problem in distributed coherent aperture radar. In this paper, the wideband dechirping echo and coherent parameters model are built firstly. Then a novel coherent parameters estimation method based on MUSIC and Kalman filter is proposed. Finally, simulations are carried out to illustrate the performance of the proposed method under low SNR.

关键词： Kalman filters

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Object classification of remote sensing images based on BOV

Object classification of remote sensing images based on BOV

引用

IET International Radar Conference 2015

作者： Zhao, Boya Shi, Hao Chen, Liang Chen, He Bi, Fukun Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China North China University of Technology Beijing100144 China

ISBN: (纸本)9781849199940

In order to classify the remote sensing land-use objects efficiently with the very high resolution (VHR) remote sensing images, this letter proposes a remote sensing object classification method based on bag of visual words (BOV) model. This method combines the scale invariant feature transform (SIFT) feature and the texture feature as remote sensing words. Then, the remote sensing words are used for generating word frequency histograms. The histogram is the bridge of the remote sensing words and the classifier. At last, in the classifier design section, the histogram intersection kernel (HIK) is adopted in the SVM. We use the proposed classification method to classify the UC Merced dataset and self-made dataset. Experimental results show that the proposed remote sensing object classification method yields better classification than the existing methods in terms of the classification accuracy.

关键词： Classification (of information)

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