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ORBIT ERROR ESTIMATION IN GROUND-BASED RADAR LUNAR 3D IMAGING BASED ON MINIMUM ENTROPY

ORBIT ERROR ESTIMATION IN GROUND-BASED RADAR LUNAR 3D IMAGIN...

引用

IET International Radar Conference 2023, IRC 2023

作者： Yang, Yuewen Zhu, Kaiwen Wang, Zhen Ding, Zegang Radar Research Laboratory 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 Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839539954

Ground-based (GB) radar is an effective approach in lunar observation. In GB radar lunar three-dimensional (3D) high-resolution imaging, orbital measurement error will degrade the image quality, and should be estimated and compensated. In this manuscript, an orbit error estimation and compensation method for GB radar lunar 3D imaging based on minimum entropy is proposed. First, echo model considering orbit error is established. Thereafter an autofocus algorithm based on back projection and minimum entropy is proposed to acquire fine-resolved image. Furthermore, particle swarm optimization (PSO) algorithm based on dynamic inertia weight is used to estimate the optimal compensation parameter to minimize the image entropy. Finally, computer simulation results validate the effectiveness of the proposed method. © The Institution of Engineering & technology 2023.

关键词： Radar imaging

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Ground-based Radar Three-Dimensional Imaging for Moon under Sparse Observations

Ground-based Radar Three-Dimensional Imaging for Moon under ...

引用

IET International Radar Conference 2023, IRC 2023

作者： Liu, Peiyao Zhu, Kaiwen Wang, Zhen Ding, Zegang Radar Research Laboratory 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 Chongqing Innovation Center Beijing Institute of Technology Chongqing China

ISBN: (纸本)9781839539954

Ground-based radar system (GBRs) is a powerful tool to obtain three-dimensional (3-D) imagery of the interested celestial bodies, such as the moon. However, in 3-D moon imaging with GBRs, positions for observation are distributed sparsely, and it will lead to imaging ambiguity in height dimension. In this article, a ground-based radar 3-D imaging method for moon under sparse observation is proposed. First, baseline distribution is analyzed, and an optimal baseline selection algorithm based on spatial baseline density maximization is applied. Then, a tomographic 3-D imaging algorithm is discussed, and compressive sensing (CS) technique is used to recover the elevation signal under sparse observation. Moreover, computer simulations are conducted and validate the proposed method. © The Institution of Engineering & technology 2023.

关键词： Radar imaging

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GEOSYNCHRONOUS SAR 3-D TARGET RECONSTRUCTION BASED ON MULTI-ANGLE OBSERVATION

GEOSYNCHRONOUS SAR 3-D TARGET RECONSTRUCTION BASED ON MULTI-...

引用

IET International Radar Conference 2023, IRC 2023

作者： Zhu, Kaiwen Zhang, Tianyi Li, Linghao Ding, Zegang Radar Research Laboratory 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 Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781839539954

Geosynchronous synthetic aperture radar (GEO SAR) has the ability of multi-angle observation, and the potential to reconstruct the three-dimensional (3-D) structure of target. To fully utilize this ability, a 3-D target reconstruction method based on multi-angle observation and forward projection is proposed. The core idea of the proposed method is to determine whether target exists on a 3-D position by forward projecting the 3-D position onto the multi-angle SAR images. The proposed method is well validated via simulation and real data experiment. © The Institution of Engineering & technology 2023.

关键词： 3D reconstruction

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Marine Ship Detection Method for SAR Image Based on Improved Faster RCNN

Marine Ship Detection Method for SAR Image Based on Improved...

引用

2021 SAR in Big Data Era, BIGSARDATA 2021

作者： Chai, Bingqian Chen, Liang Shi, Hao He, Cheng Beijing Key Laboratory of Embedded Real-time Information Processing Technology Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665401234

Due to the multi-view imaging principle of synthetic aperture radar (SAR), its imaging process is not limited by any time or any bad weather. The detection of marine ship for SAR image is a very important application in both military and private applications. A marine ship detection method in SAR image about an improved Faster RCNN-based approach is proposed. First, the deepest semantic features of SAR image extracted by Faster RCNN contain less target information and small targets may be ignored, so that we fuse the deepest feature and shallower features in the feature extraction network;Secondly, because the redundant information in the features will produce false alarms, we embed the Convolutional Block Attention Module (CBAM) in the feature extraction network to extract more effective features;Finally, we use bilinear interpolation to obtain floating-point coordinates to optimize RoI pooling which uses rounding quantization, so the error mapping caused by quantization will be reduced. The algorithm of this paper is tested on the SSDD public dataset, and the AP is increased from 0.79 to 0.89. The results demonstrate that the algorithm introduced in this paper has a very significant performance improvement for detecting ship-like targets from SAR images. © 2021 IEEE.

关键词： Synthetic aperture radar

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A near-field back-projection algorithm for wall penetrating SAR

A near-field back-projection algorithm for wall penetrating ...

引用

IET International Radar Conference 2015

作者： Liu, Wei Wei, Wei Zheng, Meng Xiang, Yin Ding, Zegang Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology China No. 203 Research Institute of China Ordance Industries Xi'an Shaanxi710065 China

ISBN: (纸本)9781849199940

We are going to develop a handheld wall penetrating SAR (WPSAR) to investigate the small shallowly buried objects such as thin wires, cables and so on. The WPSAR will be working very close to the wall surface, and the objects of interest sometimes buried inside the induced near-filed region of the probe. As a result, the traditional far-field SAR imaging algorithm cannot be used. Thus, a useful near-field back-projection algorithm is investigated in this paper, which backprojects the probe's aperture field into the wall, instead of backprojecting the echo signal along the wave propagation track as it is done in the traditional BP. A full wave simulation data given by CST is used to validate our algorithm. The result shows that the proposed near-field BP algorithm gives a correct imaging result while the traditional one fails.

关键词： Synthetic aperture radar

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Research on SAR Image Matching Based on SAR-Harris Detector and Adaptive Locally-Affine Matching

Research on SAR Image Matching Based on SAR-Harris Detector ...

引用

IET International Radar Conference 2023, IRC 2023

作者： Wu, Guanghui Shi, Hao Chen, Fan Pan, Hongxin Chen, Liang 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)9781839539954

Synthetic aperture radar (SAR) image matching is an essential step in SAR image processing. The synthetic aperture radar-scale invariant feature transform (SAR-SIFT), which combines the ratio of exponentially weighted averages (ROEWA) operator with multiscale Harris detection and employs Random Sample Consensus (RANSAC) for matching and filtering, has shown promising results. However, SAR-SIFT suffers from low matching efficiency in specific scenarios, and RANSAC exhibits strong randomness and potential problems of non-convergence. To address these problems, this paper introduces an approach that combines scale-space layers reduction in the SAR-Harris detector with the efficient Adaptive Locally-Affine Matching (AdaLAM) to enhance SAR image matching performance. The proposed SAR-SIFT-AdaLAM method is experimentally evaluated on two sets of different SAR images for matching, and the results indicate an improvement of approximately 25% in the number of matching points compared to the SAR-SIFT, along with a reduction of about 30% in matching time, demonstrating its effectiveness. © The Institution of Engineering & technology 2023.

关键词： Synthetic aperture radar

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Efficiency balanced matrix transpose method for sliding spotlight SAR imaging processing

Efficiency balanced matrix transpose method for sliding spot...

引用

IET International Radar Conference 2018, IRC 2018

作者： Sun, Tianyuan Xie, Yizhuang Li, Bingyi 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

Matrix transposition is a very critical operation in synthetic aperture radar (SAR) imaging systems. This study presents an improved corner turning memory solution for real-time SAR imaging processing. Based on the sub-matrix three-dimensional mapping method, the efficiency of matrix transposing is greatly increased. However, in sliding spotlight mode, a novel SAR imaging mode, the amount of raw data is increased too large to directly use the above method. In this study, a joint address mapping strategy for two pieces of double data rate 3 synchronous dynamic random-access memory is used to meet the needs of the amount of data and make up for the lack of original method. The experimental results show that this method can get an improved and balanced two-dimensional access efficiency for sliding spotlight mode SAR imaging processing. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Mapping

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Interface conversion and extension based on FPGA in high-speed real-time signal processing system

Interface conversion and extension based on FPGA in high-spe...

引用

IET International Radar Conference 2015

作者： Sun, Hao Chen, Fang Hu, Shanqing Li, Xingming Sun, Yujie State Key Laboratory of Explosion Science and Technology Beijing Institute of Technology China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology China Robfly Research Center Electromechanical College Beijing Institute of Technology China

ISBN: (纸本)9781849199940

The radar systems have been so significant for both civil use and national defense, and adopting localized processor has become critical for a country, especially for the area related to the national defense. In this paper, we utilize localized BWDSP100 as the main processor, and implement a high-speed and real-time signal processing system by using BWDSP100 + FPGA framework. We use FPGA to realize the interface conversions and extensions, which enhance the reading bandwidth of the DDR2 interface from 235MB/s to 562MB/s. Besides that, we also integrate highspeed serial buses, such as PCIe interface of 243MB/s and SRIO interface of 344MB/s, for communications in or between boards. The system has been used in several projects, and works well.

关键词： Field programmable gate arrays (FPGA)

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Hybrid optimisation method of improved genetic algorithm and IFT for linear thinned array

Hybrid optimisation method of improved genetic algorithm and...

引用

IET International Radar Conference 2018, IRC 2018

作者： Wang, Zheng Sun, Yuze Yang, Xiaopeng Li, Shuai Beijing Key Laboratory of Embedded Real-time Information Processing Technology School of Information and Electronics Beijing Institute of Technology Beijing China Department of Electronic Engineering Tsinghua University Beijing China

The array thinning technique can greatly reduce the number of the array elements while keeping the performance of the array almost the same. However, the existing algorithms have slow convergence rates and are easy to fall into local optimum. To improve the optimisation performance, a hybrid method based on improved genetic algorithm (GA) and iterative Fourier transform (IFT) technique for linear thinned array is proposed in this study. The population is divided into improved GA group and IFT group according to the convergence of the population and different operations can be done paralleled to generate offspring in each iteration. In the improved GA processing, adaptive crossover rate and mutation rate are used. The mechanism that keeps the fill factor stable is removed for larger search range. The IFT processing is executed paralleled for fast convergence velocity. The proposed hybrid method can obtain the fast convergence velocity and avoid being trapped into the local optimum by the combination of the two approaches. Several examples are simulated to validate the performance of the proposed method. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Genetic algorithms

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Optical Remote Sensing Image Waters Extraction technology Based on Deep Learning Context-Unet

Optical Remote Sensing Image Waters Extraction Technology Ba...

引用

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

作者： Yan, Ruoda Dong, Shan Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China Engineering Center of Digital Audio and Video Communication University of China Beijing100024 China

ISBN: (纸本)9781728123455

The optical remote sensing images are used to sea-land segmentation which is a difficult task. Due to general deep learning based methods required a large number of refined annotation, however, a large scale optical remote sensing images annotation is very expensive. Therefore, the Context-Unet is proposed to produce accurate sea-land segmentation results by a few annotated training samples. In this paper, we apply the Context-Unet network to the watershed extraction. On the basis of this, we re-compile the loss function to improve the accuracy of watershed extraction. Example: Finally, the date collected from Google Earth service is used to train and test this paper proposed Context-Unet and state-o-the-art methods. The experiments proved that the proposed method outperforms than other methods, and it can achieve 98% precision and 97% recall ratios. © 2019 IEEE.

关键词： Object detection

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