Pub Date : 2019-11-01DOI: 10.1109/APSAR46974.2019.9048489
Jinyu Bao, Xiaoling Zhang, Xinxin Tang, Jun Shi, Shunjun Wei
As an important applications of synthetic aperture radar (SAR), slow moving target detection is causing more concern from people. Commonly, with the increase of computer computational efficiency and utilization of GPU, convolutional neural network has been becoming an efficient approach for target detection and classification. Here we propose a method using Faster R-CNN to detect the slow moving target in SAR images. When using existing datasets to detect moving targets, the detection accuracy is low due to the small defocusing of slow moving targets. So we use the bidirectional imaging mode to create the dataset. By increasing the displacement, it is more conducive to detect slow moving targets. At the same time, neural network provides a feasible way for target detection in this mode. In order to close to the reality echo, we use FEKO to simulate the target echo and use measured ground data to generate the ground echo. Deep learning combined with the forward and backward beams can detect slow moving target more effectively. The simulation results validate the effectiveness of the proposed method.
{"title":"SAR-GMTI for Slow Moving Target Based on Neural Network","authors":"Jinyu Bao, Xiaoling Zhang, Xinxin Tang, Jun Shi, Shunjun Wei","doi":"10.1109/APSAR46974.2019.9048489","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048489","url":null,"abstract":"As an important applications of synthetic aperture radar (SAR), slow moving target detection is causing more concern from people. Commonly, with the increase of computer computational efficiency and utilization of GPU, convolutional neural network has been becoming an efficient approach for target detection and classification. Here we propose a method using Faster R-CNN to detect the slow moving target in SAR images. When using existing datasets to detect moving targets, the detection accuracy is low due to the small defocusing of slow moving targets. So we use the bidirectional imaging mode to create the dataset. By increasing the displacement, it is more conducive to detect slow moving targets. At the same time, neural network provides a feasible way for target detection in this mode. In order to close to the reality echo, we use FEKO to simulate the target echo and use measured ground data to generate the ground echo. Deep learning combined with the forward and backward beams can detect slow moving target more effectively. The simulation results validate the effectiveness of the proposed method.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"105 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131315963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/APSAR46974.2019.9048258
Xiaoning Hu, M. Xiang, Bingnan Wang, Xikai Fu
Interferometric synthetic aperture radar (InSAR) can be used to extract digital elevation model (DEM) with high accuracy. However, the side looking geometry of synthetic aperture radar (SAR) may cause geometric distortions such as shadow and layover in the mountainous terrain, which will reduce the quality of generated DEM. Fusion of two or more different aspects of InSAR data can deal with this problem. We propose an InSAR DEM reconstruction method based on backprojection (BP) algorithm in two converse flights. This method utilizes the feature of BP algorithm that geocoding has been realized in imaging process to simplify the fusion process of multi-aspect InSAR data. In addition, an iterative DEM extraction method is introduced to improve DEM accuracy. Experimental results verify the effectiveness of the proposed method.
{"title":"InSAR DEM Reconstruction Based on Backprojection Algorithm in Two Converse Flights","authors":"Xiaoning Hu, M. Xiang, Bingnan Wang, Xikai Fu","doi":"10.1109/APSAR46974.2019.9048258","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048258","url":null,"abstract":"Interferometric synthetic aperture radar (InSAR) can be used to extract digital elevation model (DEM) with high accuracy. However, the side looking geometry of synthetic aperture radar (SAR) may cause geometric distortions such as shadow and layover in the mountainous terrain, which will reduce the quality of generated DEM. Fusion of two or more different aspects of InSAR data can deal with this problem. We propose an InSAR DEM reconstruction method based on backprojection (BP) algorithm in two converse flights. This method utilizes the feature of BP algorithm that geocoding has been realized in imaging process to simplify the fusion process of multi-aspect InSAR data. In addition, an iterative DEM extraction method is introduced to improve DEM accuracy. Experimental results verify the effectiveness of the proposed method.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131503634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/APSAR46974.2019.9048382
Chenwei Wang, Jifang Pei, Rufei Wang, Yulin Huang, Jianyu Yang
Satellite remote sensing technology has always received wide attention for its developing performance of earth observation. Ship detection and classification based on spaceborne SAR images has been an attractive and intractable topic because the wide sea area is too complex to detect and classify all the objective ships. In this paper, a new ship detection and classification method for complex sea surface is presented. It adopts the visual saliency detection method based on spectral residual to obtain the locations of the regions of interest(ROIs) containing ships. And the morphology filter is employed to exclude a part of false alarm targets (FATs). Then, the types of the ships are classified based on convolution neural network (CNN). Finally, the locations and types of ships in large sea SAR images are acquired. Experimental results based on measured spaceborne SAR images have shown the effectiveness and accuracy of the proposed method.
{"title":"A new ship detection and classification method of spaceborne SAR images under complex scene","authors":"Chenwei Wang, Jifang Pei, Rufei Wang, Yulin Huang, Jianyu Yang","doi":"10.1109/APSAR46974.2019.9048382","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048382","url":null,"abstract":"Satellite remote sensing technology has always received wide attention for its developing performance of earth observation. Ship detection and classification based on spaceborne SAR images has been an attractive and intractable topic because the wide sea area is too complex to detect and classify all the objective ships. In this paper, a new ship detection and classification method for complex sea surface is presented. It adopts the visual saliency detection method based on spectral residual to obtain the locations of the regions of interest(ROIs) containing ships. And the morphology filter is employed to exclude a part of false alarm targets (FATs). Then, the types of the ships are classified based on convolution neural network (CNN). Finally, the locations and types of ships in large sea SAR images are acquired. Experimental results based on measured spaceborne SAR images have shown the effectiveness and accuracy of the proposed method.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130075243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/APSAR46974.2019.9048322
Hao Wu
SAR (Synthetic Aperture Radar) satellites can perform reconnaissance on specific areas in all directions. Generally speaking, the scope of reconnaissance is smaller than that of passive reconnaissance. Therefore, orbit and constellation design are more important. Here we use the maximum coverage gap to measure the reconnaissance efficiency of the SAR satellite constellation and the simulation technology is studied. The results show that the change of orbital inclination has a great influence on the maximum revisit interval. The visible range of SAR satellite has a great influence on the maximum revisit interval, as well as the number of orbital planes. Based on this method, the simulation of the space-borne SAR is carried out. The orbit design and optimization of reconnaissance mission design scheme can provide a convenient and effective support platform for the simulation analysis of space-borne SAR missions.
{"title":"Simulation Technology of Spaceborne SAR Reconnaissance Effeciency","authors":"Hao Wu","doi":"10.1109/APSAR46974.2019.9048322","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048322","url":null,"abstract":"SAR (Synthetic Aperture Radar) satellites can perform reconnaissance on specific areas in all directions. Generally speaking, the scope of reconnaissance is smaller than that of passive reconnaissance. Therefore, orbit and constellation design are more important. Here we use the maximum coverage gap to measure the reconnaissance efficiency of the SAR satellite constellation and the simulation technology is studied. The results show that the change of orbital inclination has a great influence on the maximum revisit interval. The visible range of SAR satellite has a great influence on the maximum revisit interval, as well as the number of orbital planes. Based on this method, the simulation of the space-borne SAR is carried out. The orbit design and optimization of reconnaissance mission design scheme can provide a convenient and effective support platform for the simulation analysis of space-borne SAR missions.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115990616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/APSAR46974.2019.9048268
Yu Guo, Wei Yang, Jie Chen, Chunsheng Li, Xiaokun Sun
Azimuth multi-channels is widely used for high-resolution and wide-swath recently, especially for the purpose of interferometry processing. However, due to the reconstruction of non-uniformly azimuth signal, the classical phase-preserving algorithm does not work well. In this paper, a phase-preserving imaging algorithm for azimuth multi-channel spaceborne SAR data processing is proposed. Firstly, combined with the reconstruction operation, the effect on phase-preserving accuracy is analyzed in detail, with the discussion of the equivalent phase center position. Then, the novel phase-preserving algorithm is addressed, which can accurately compensate the phase errors, including the constant phase term, the linear phase term introduced by the shifting zero-Doppler frequency, the residual cubic phase error along range direction, and the nonuniform sampling phase error after range-compression. Finally, simulation results verify the effectiveness of the proposed algorithm.
{"title":"A phase-preserving imaging algorithm for azimuth multi-channel spaceborne SAR data processing","authors":"Yu Guo, Wei Yang, Jie Chen, Chunsheng Li, Xiaokun Sun","doi":"10.1109/APSAR46974.2019.9048268","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048268","url":null,"abstract":"Azimuth multi-channels is widely used for high-resolution and wide-swath recently, especially for the purpose of interferometry processing. However, due to the reconstruction of non-uniformly azimuth signal, the classical phase-preserving algorithm does not work well. In this paper, a phase-preserving imaging algorithm for azimuth multi-channel spaceborne SAR data processing is proposed. Firstly, combined with the reconstruction operation, the effect on phase-preserving accuracy is analyzed in detail, with the discussion of the equivalent phase center position. Then, the novel phase-preserving algorithm is addressed, which can accurately compensate the phase errors, including the constant phase term, the linear phase term introduced by the shifting zero-Doppler frequency, the residual cubic phase error along range direction, and the nonuniform sampling phase error after range-compression. Finally, simulation results verify the effectiveness of the proposed algorithm.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122474504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/APSAR46974.2019.9048305
Junying Yang, Xiaolan Qiu, L. Zhong, C. Ding, Lijia Huang, H. Chen
Gaofen-3 (GF-3) is the first Chinese multichannel synthetic aperture radar (SAR) sensor that can operate in the dual receive channel (DRC) mode. Different from the traditional single-channel SAR system, the multichannel SAR system can overcome the inherent limitation to achieve high-resolution and wide-swath (HRWS) at the same time. However, the key challenge it faces is false target suppression. Especially for the moving vessels on the ocean, the existence of false targets will increase false alarm probability and affect the interpretation of SAR images. In this paper, the method of integration of detection, velocity estimation, location, and imaging for moving targets in the HRWS SAR system is proposed as well as applied to get an unambiguous image. The simulation and GF-3 real data experimental results show the validity of the method.
{"title":"Unambiguous Imaging for Moving Targets in Maritime Scenarios with Dual Receive Channel Mode of GF-3 Satellite","authors":"Junying Yang, Xiaolan Qiu, L. Zhong, C. Ding, Lijia Huang, H. Chen","doi":"10.1109/APSAR46974.2019.9048305","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048305","url":null,"abstract":"Gaofen-3 (GF-3) is the first Chinese multichannel synthetic aperture radar (SAR) sensor that can operate in the dual receive channel (DRC) mode. Different from the traditional single-channel SAR system, the multichannel SAR system can overcome the inherent limitation to achieve high-resolution and wide-swath (HRWS) at the same time. However, the key challenge it faces is false target suppression. Especially for the moving vessels on the ocean, the existence of false targets will increase false alarm probability and affect the interpretation of SAR images. In this paper, the method of integration of detection, velocity estimation, location, and imaging for moving targets in the HRWS SAR system is proposed as well as applied to get an unambiguous image. The simulation and GF-3 real data experimental results show the validity of the method.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122926258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/APSAR46974.2019.9048257
Zhenning Zhang, Weidong Yu, M. Zheng, Zi-Xuan Zhou, Huimin Zheng
In multichannel synthetic aperture radar (SAR) Ground Moving Target Indication (GMTI) systems, Doppler centroid (DC) is an essential parameter for spectral reconstruction and image focusing. However, conventional DC estimator for stationary scene faces many problems in moving target with multichannel SAR, such as low sampling rate and channels selection. To estimate the baseband DC of moving target, a modified CDE method for multichannel SAR GMTI system is proposed in this paper. Simulation results demonstrate the effectiveness of this method.
{"title":"Baseband Doppler Centroid Estimation for Ground Moving Target with Multichannel SAR","authors":"Zhenning Zhang, Weidong Yu, M. Zheng, Zi-Xuan Zhou, Huimin Zheng","doi":"10.1109/APSAR46974.2019.9048257","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048257","url":null,"abstract":"In multichannel synthetic aperture radar (SAR) Ground Moving Target Indication (GMTI) systems, Doppler centroid (DC) is an essential parameter for spectral reconstruction and image focusing. However, conventional DC estimator for stationary scene faces many problems in moving target with multichannel SAR, such as low sampling rate and channels selection. To estimate the baseband DC of moving target, a modified CDE method for multichannel SAR GMTI system is proposed in this paper. Simulation results demonstrate the effectiveness of this method.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122272638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/APSAR46974.2019.9048479
Xin Qi, Yun Zhang, Yicheng Jiang
This paper presents bistatic synthetic aperture radar imaging preliminary results with GNSS transmitters and low-orbit satellite receivers. The establishment of the scene model which low-orbit satellite receives the GNSS satellite transmitting signals after being reflected by the target is achieved by STK. The “CoverDefinition” module is used to further analyze the GNSS-BiSAR visible area coverage during satellites motion. BP imaging algorithm and improved series reversion method are compared and their respective characteristics and applicable conditions are discussed.
{"title":"Bistatic SAR Imaging with GNSS Transmitters and Low-Orbit Areceivers","authors":"Xin Qi, Yun Zhang, Yicheng Jiang","doi":"10.1109/APSAR46974.2019.9048479","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048479","url":null,"abstract":"This paper presents bistatic synthetic aperture radar imaging preliminary results with GNSS transmitters and low-orbit satellite receivers. The establishment of the scene model which low-orbit satellite receives the GNSS satellite transmitting signals after being reflected by the target is achieved by STK. The “CoverDefinition” module is used to further analyze the GNSS-BiSAR visible area coverage during satellites motion. BP imaging algorithm and improved series reversion method are compared and their respective characteristics and applicable conditions are discussed.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126937405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/APSAR46974.2019.9048475
Liting Liang, Yunhua Zhang, Dong Li
This paper extends the range of polarization orientation angle (POA) estimation of polarimetric synthetic aperture radar (PolSAR) data from conventional [−45°,45°] to [−90°, 90°] over steep terrain, combining with the physical scattering mechanisms of natural terrain surface. The algorithm achieves consistent estimation with the widely-used circular polarization algorithm (CPA) over flat area, but avoids the POA wrapping caused by the restriction of CPA over precipitous area, which is substantiated by both simulated data of Bragg scattering and PolSAR data of NASA/JPL AIRSAR.
{"title":"Range Extension of Polarization Orientation Angle Estimation over Steep Terrain","authors":"Liting Liang, Yunhua Zhang, Dong Li","doi":"10.1109/APSAR46974.2019.9048475","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048475","url":null,"abstract":"This paper extends the range of polarization orientation angle (POA) estimation of polarimetric synthetic aperture radar (PolSAR) data from conventional [−45°,45°] to [−90°, 90°] over steep terrain, combining with the physical scattering mechanisms of natural terrain surface. The algorithm achieves consistent estimation with the widely-used circular polarization algorithm (CPA) over flat area, but avoids the POA wrapping caused by the restriction of CPA over precipitous area, which is substantiated by both simulated data of Bragg scattering and PolSAR data of NASA/JPL AIRSAR.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126350208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1109/APSAR46974.2019.9048561
Zhenyu Guo, Hongbo Zhang, Shaohua Ye
Circular SAR is able to achieve omni-directional observation and high-resolution imaging of targets. However, the traditional frequency-domain based imaging algorithm is not suitable for complicated curve trajectory. Moreover the time domain based back-projection (BP) algorithm is applicable but time consuming. Fast factorized back-projection (FFBP) algorithm based on aperture decomposition and image fusion can balance computational efficiency and accuracy. In this paper, we proposed a modified FFBP algorithm for circular SAR imaging. The principal improvement is the usage of Cartesian coordinate imaging and nonuniform fast Fourier transform (NUFFT) interpolation. First, sub-aperture BP imaging is implemented on local Cartesian coordinate system. Then azimuth bandwidth is compressed with a spatial variant phase function to reduce the sampling rate. Next the NUFFT interpolation method is applied during sub-images fusion to further improve the efficiency of the algorithm. Finally, through simulation and real data experiments, the correctness and accuracy of the algorithm is verified.
{"title":"Cartesian based FFBP algorithm for circular SAR using NUFFT interpolation","authors":"Zhenyu Guo, Hongbo Zhang, Shaohua Ye","doi":"10.1109/APSAR46974.2019.9048561","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048561","url":null,"abstract":"Circular SAR is able to achieve omni-directional observation and high-resolution imaging of targets. However, the traditional frequency-domain based imaging algorithm is not suitable for complicated curve trajectory. Moreover the time domain based back-projection (BP) algorithm is applicable but time consuming. Fast factorized back-projection (FFBP) algorithm based on aperture decomposition and image fusion can balance computational efficiency and accuracy. In this paper, we proposed a modified FFBP algorithm for circular SAR imaging. The principal improvement is the usage of Cartesian coordinate imaging and nonuniform fast Fourier transform (NUFFT) interpolation. First, sub-aperture BP imaging is implemented on local Cartesian coordinate system. Then azimuth bandwidth is compressed with a spatial variant phase function to reduce the sampling rate. Next the NUFFT interpolation method is applied during sub-images fusion to further improve the efficiency of the algorithm. Finally, through simulation and real data experiments, the correctness and accuracy of the algorithm is verified.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127832450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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