Pub Date : 2019-11-01DOI: 10.1109/apsar46974.2019.9048420
Jin-Tong Zhan, Zhi-hui Zhang
For high resolution synthetic aperture radar (SAR) applications, an active phased antenna module has been developed, where a broadband, highly efficient waveguide slot antenna is used as its passive radiator. A prototype has been fabricated and tested. Excellent performance is achieved through experiments, which thereby validates the concept of design.
{"title":"Broadband Antenna Array for SAR Applications","authors":"Jin-Tong Zhan, Zhi-hui Zhang","doi":"10.1109/apsar46974.2019.9048420","DOIUrl":"https://doi.org/10.1109/apsar46974.2019.9048420","url":null,"abstract":"For high resolution synthetic aperture radar (SAR) applications, an active phased antenna module has been developed, where a broadband, highly efficient waveguide slot antenna is used as its passive radiator. A prototype has been fabricated and tested. Excellent performance is achieved through experiments, which thereby validates the concept of design.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"18 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":"128965706","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}
Since 2011, The area of the Salt Lake was increasing due to the bursting of the Zonag Lake burst. The expansion of the lake would accelerate the melting of permafrost, leading to more severe surface deformation around the lake. In this paper, the deformation of permafrost area around the Salt Lake have been retrieved applying time-series InSAR method with Sentinel-1A data from 2014. 12 to 2018.12. The preliminary result shows that obvious deformation has been observed around the Salt Lake, with the maximum deformation rate larger than −20 mm/year. Future work will focus on analyzing the relationship between the deformation pattern and the area extend of the Salt Lake.
{"title":"Deformation Monitoring Around Salt Lake in Qinghai-Tibet Plateau Using Time-Series InSAR with Sentinel-1A Images from 2014–2018","authors":"Zhengjia Zhang, Xiuguo Liu, Mengmeng Wang, Zhijie Wu, Qihao Chen, Xin Zhou","doi":"10.1109/APSAR46974.2019.9048260","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048260","url":null,"abstract":"Since 2011, The area of the Salt Lake was increasing due to the bursting of the Zonag Lake burst. The expansion of the lake would accelerate the melting of permafrost, leading to more severe surface deformation around the lake. In this paper, the deformation of permafrost area around the Salt Lake have been retrieved applying time-series InSAR method with Sentinel-1A data from 2014. 12 to 2018.12. The preliminary result shows that obvious deformation has been observed around the Salt Lake, with the maximum deformation rate larger than −20 mm/year. Future work will focus on analyzing the relationship between the deformation pattern and the area extend of the Salt Lake.","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":"129118583","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/APSAR46974.2019.9048290
Yi Du, Kefei Liao, S. Ouyang, Gaojian Huang, Jingjing Li, Ningbo Xie
In this paper, a novel frame combining frequency diversity with inverse synthetic aperture is proposed. In this frame, the transmitted single frequency signals is selected among diverse frequencies at different observed time. These selected frequencies can synthesize a wideband signal, thus achieving a high distance resolution. And in the azimuth direction, the resolution can be obtained by the relative motion between the radar and the target. Therefore, the proposed frame has the ability of two-dimensional imaging for targets. For the proposed frame, furthermore, an ISAR imaging model based on synthetic wide-band signals is established, and an improved two-dimensional ISAR imaging algorithm based on the backward projection (BP) imaging algorithm is proposed. Simulation show that the improved two-dimensional ISAR imaging algorithm can obtain two-dimensional imaging of multiple moving targets. Therefore, from the perspective of applications, the proposed frame can reduce the hardware complexity and cost of transmitter/receiver when compared with the existing ISAR imaging systems.
{"title":"Two-Dimensional Imaging Using Frequency Diversity with Inverse Synthetic Aperture","authors":"Yi Du, Kefei Liao, S. Ouyang, Gaojian Huang, Jingjing Li, Ningbo Xie","doi":"10.1109/APSAR46974.2019.9048290","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048290","url":null,"abstract":"In this paper, a novel frame combining frequency diversity with inverse synthetic aperture is proposed. In this frame, the transmitted single frequency signals is selected among diverse frequencies at different observed time. These selected frequencies can synthesize a wideband signal, thus achieving a high distance resolution. And in the azimuth direction, the resolution can be obtained by the relative motion between the radar and the target. Therefore, the proposed frame has the ability of two-dimensional imaging for targets. For the proposed frame, furthermore, an ISAR imaging model based on synthetic wide-band signals is established, and an improved two-dimensional ISAR imaging algorithm based on the backward projection (BP) imaging algorithm is proposed. Simulation show that the improved two-dimensional ISAR imaging algorithm can obtain two-dimensional imaging of multiple moving targets. Therefore, from the perspective of applications, the proposed frame can reduce the hardware complexity and cost of transmitter/receiver when compared with the existing ISAR imaging systems.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"509 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":"132480609","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/apsar46974.2019.9048365
Yang Zhou, Aiguo Shen, Daping Bi, Yang Zhang
In view of the insufficient research on SAR vibrating target location, an algorithm for SAR vibrating target location is proposed in this paper. The range location of vibrating target is realized by accumulating the amplitude of the DPCA signal along the azimuth direction, and azimuth location is realized by calculating the interferometry phase of the cancellation signals. In this paper, the DPCA technique and the accumulation method are used to improve the performance of the anti-clutter and anti-noise. The location results of the simulation experiment are in good agreement with the theoretical position of the vibration targets, which proves the correctness of the algorithm.
{"title":"Vibration Target Location Algorithm Based on Multi-Channel SAR","authors":"Yang Zhou, Aiguo Shen, Daping Bi, Yang Zhang","doi":"10.1109/apsar46974.2019.9048365","DOIUrl":"https://doi.org/10.1109/apsar46974.2019.9048365","url":null,"abstract":"In view of the insufficient research on SAR vibrating target location, an algorithm for SAR vibrating target location is proposed in this paper. The range location of vibrating target is realized by accumulating the amplitude of the DPCA signal along the azimuth direction, and azimuth location is realized by calculating the interferometry phase of the cancellation signals. In this paper, the DPCA technique and the accumulation method are used to improve the performance of the anti-clutter and anti-noise. The location results of the simulation experiment are in good agreement with the theoretical position of the vibration targets, which proves the correctness of the algorithm.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"18 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":"130401232","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/APSAR46974.2019.9048279
Yuanyuan Zhou, Tingjun Chen, Jinchuan Tian, Zenan Zhou, Chen Wang, X. Yang, Jun Shi
Deep learning networks are widely being applied to remote sensing image recognition and have achieved promising results. In this paper, we researched the influence of background with different scattering characteristics for synthetic aperture radar (SAR) target recognition based on convolutional neural network (CNN). Firstly, a two-parameter CFAR image segmentation method based on Weibull distribution was used to extracted SAR target and its shadow. And then, SAR datasets with road, farmland and grassland background environment is synthesized to analyze the CNN classifier. Experiments results show that the method by mixing training sets with different background together can improve the recognization rate when the backgrounds are complex.
{"title":"Complex Background SAR Target Recognition Based on Convolution Neural Network","authors":"Yuanyuan Zhou, Tingjun Chen, Jinchuan Tian, Zenan Zhou, Chen Wang, X. Yang, Jun Shi","doi":"10.1109/APSAR46974.2019.9048279","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048279","url":null,"abstract":"Deep learning networks are widely being applied to remote sensing image recognition and have achieved promising results. In this paper, we researched the influence of background with different scattering characteristics for synthetic aperture radar (SAR) target recognition based on convolutional neural network (CNN). Firstly, a two-parameter CFAR image segmentation method based on Weibull distribution was used to extracted SAR target and its shadow. And then, SAR datasets with road, farmland and grassland background environment is synthesized to analyze the CNN classifier. Experiments results show that the method by mixing training sets with different background together can improve the recognization rate when the backgrounds are complex.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"17 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":"131650508","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/APSAR46974.2019.9048509
Tong Zheng, Jun Wang, Peng Lei
In view of synthetic aperture radar (SAR) target detection, traditional methods are based on hand-crafted feature extraction and classifier. Besides, deep learning (DL) based methods are research hotspots in recent year. However, their shortcomings cannot be neglected, i.e. detection accuracy of traditional method needs to be improved and DL features are difficult to interpret. To overcome these problems, a target detection method with multi-features in SAR imagery is proposed in this paper. It consists of two parallel sub-channels. DL features and hand-crafted features are extracted in these channels, respectively. Here, convolutional neural network (CNN) model is applied to capture DL features of original SAR images. Deep neural network (NN) is used to further analyze hand-crafted features. Furthermore, two sub-channel features are concatenated together in the main channel. After several layers network processing, fused deep features are extracted. Finally, softmax classifier is applied to discriminate ship target. According to the experiments based on Sentinel-1 SAR data, we can find that the detection performance is improved by the proposed method.
{"title":"Deep learning based target detection method with multi-features in SAR imagery","authors":"Tong Zheng, Jun Wang, Peng Lei","doi":"10.1109/APSAR46974.2019.9048509","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048509","url":null,"abstract":"In view of synthetic aperture radar (SAR) target detection, traditional methods are based on hand-crafted feature extraction and classifier. Besides, deep learning (DL) based methods are research hotspots in recent year. However, their shortcomings cannot be neglected, i.e. detection accuracy of traditional method needs to be improved and DL features are difficult to interpret. To overcome these problems, a target detection method with multi-features in SAR imagery is proposed in this paper. It consists of two parallel sub-channels. DL features and hand-crafted features are extracted in these channels, respectively. Here, convolutional neural network (CNN) model is applied to capture DL features of original SAR images. Deep neural network (NN) is used to further analyze hand-crafted features. Furthermore, two sub-channel features are concatenated together in the main channel. After several layers network processing, fused deep features are extracted. Finally, softmax classifier is applied to discriminate ship target. According to the experiments based on Sentinel-1 SAR data, we can find that the detection performance is improved by the proposed method.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"28 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":"126696145","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/APSAR46974.2019.9048325
Dexin Li, Z. Dong, Manqing Wu, Anxi Yu, Yongsheng Zhang
Geosynchronous synthetic aperture radar (GEO SAR) is more challenging to process than the classical synthetic aperture radar (SAR) because the flight geometry is more complicated and the data is usually non-stationary. Whereas time-domain algorithms can handle general geosynchronous cases, they are very inefficient; therefore, frequency-domain methods are preferred. Several frequency-domain geosynchronous algorithms have been proposed to handle a limited number of geosynchronous cases, but a general algorithm is sought, which can handle cases such as long integration time, large scene, and especially the azimuth shift variation, which is very serious in GEO SAR imaging. In this paper, we proposed a SAR signal and range Doppler (SS-RD) algorithm to handle a more general case of GEO SAR data. The key is to use a spatial-variant (both in azimuth and range) fourth order range equation (SVRE4) to model the non-stationary, and an azimuth-invariant transform (AIT) in SAR signal (SS) domain to handle the azimuth shift variation. Simulations with the space borne radar advance simulator (SBRAS) proved that the SS-RD algorithm can handle GEO SAR data with serious azimuth shift variation.
{"title":"A Novel Processing Method for GEO SAR","authors":"Dexin Li, Z. Dong, Manqing Wu, Anxi Yu, Yongsheng Zhang","doi":"10.1109/APSAR46974.2019.9048325","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048325","url":null,"abstract":"Geosynchronous synthetic aperture radar (GEO SAR) is more challenging to process than the classical synthetic aperture radar (SAR) because the flight geometry is more complicated and the data is usually non-stationary. Whereas time-domain algorithms can handle general geosynchronous cases, they are very inefficient; therefore, frequency-domain methods are preferred. Several frequency-domain geosynchronous algorithms have been proposed to handle a limited number of geosynchronous cases, but a general algorithm is sought, which can handle cases such as long integration time, large scene, and especially the azimuth shift variation, which is very serious in GEO SAR imaging. In this paper, we proposed a SAR signal and range Doppler (SS-RD) algorithm to handle a more general case of GEO SAR data. The key is to use a spatial-variant (both in azimuth and range) fourth order range equation (SVRE4) to model the non-stationary, and an azimuth-invariant transform (AIT) in SAR signal (SS) domain to handle the azimuth shift variation. Simulations with the space borne radar advance simulator (SBRAS) proved that the SS-RD algorithm can handle GEO SAR data with serious azimuth shift variation.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"29 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":"126891402","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/APSAR46974.2019.9048261
Xiangwei Yu, Li Yang, Li Shu, Huina Huang, Fengjiao Chen
Taking the Sentinel-1A images covering the Guangyuan area as the data source, based on the research on the core algorithms such as registration, filtering and unwrapping of low-coherence SAR data in the complex terrain area, combined with the imaging features of the SAR system, the cross-correlation algorithm is used to automatically register the image deviation to less than 0.2 pixels, and minimum cost flow is used to unwrap the winding phase after the interference of the flat phase is reduced by auxiliary reference DEM. The digital elevation model (DEM) of the study area is extracted. The global and local errors of the extracted results are analyzed comprehensively. Based on piecewise statistics and regression modeling, the relationship between slope, coherence and error is discussed, and the coherence threshold and slope conditions for obtaining reliable InSAR results are determined. The results show that there is a piecewise linear relationship between slope and extraction error. The error increases most violently when the slope changes to about 50 ° and the error decreases sharply with the change of coherence and then shows a power function relationship. It has certain reference significance for using InSAR technology to measure terrain quickly.
{"title":"Extraction of DEM and Error Analysis in Mountainous Area by Using Spaceborne SAR Data","authors":"Xiangwei Yu, Li Yang, Li Shu, Huina Huang, Fengjiao Chen","doi":"10.1109/APSAR46974.2019.9048261","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048261","url":null,"abstract":"Taking the Sentinel-1A images covering the Guangyuan area as the data source, based on the research on the core algorithms such as registration, filtering and unwrapping of low-coherence SAR data in the complex terrain area, combined with the imaging features of the SAR system, the cross-correlation algorithm is used to automatically register the image deviation to less than 0.2 pixels, and minimum cost flow is used to unwrap the winding phase after the interference of the flat phase is reduced by auxiliary reference DEM. The digital elevation model (DEM) of the study area is extracted. The global and local errors of the extracted results are analyzed comprehensively. Based on piecewise statistics and regression modeling, the relationship between slope, coherence and error is discussed, and the coherence threshold and slope conditions for obtaining reliable InSAR results are determined. The results show that there is a piecewise linear relationship between slope and extraction error. The error increases most violently when the slope changes to about 50 ° and the error decreases sharply with the change of coherence and then shows a power function relationship. It has certain reference significance for using InSAR technology to measure terrain quickly.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"110 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":"126903529","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}
The resolution of bistatic SAR system is constrained by the signal bandwidth, distance, velocity and bistatic radar angle. The influence of topology structures and the strong coupling of echoes greatly limit the resolution of SAR images. And the problem of unbalanced two dimensional resolution brings difficulty and challenge to the target detection and recognition. Multi-static SAR can naturally form multiple pairs of bistatic SAR system and it fuses image information from multi-view by the design of topology structure to improve imaging resolution. To achieve optimal spatial resolution in all directions, the typical multi-static SAR geometric model is presented and the influence of topology structure on the two-dimensional resolution of bistatic and multi-static SAR is analyzed in this paper. Then, an equalization method to improve resolution for multi-static SAR is proposed. Finally, the simulation results validate the effectiveness of the proposed method.
{"title":"Two Dimensional Resolution Equalization Method in Image Domain for Airborne Multi-static SAR","authors":"Fanyun Xu, Yulin Huang, Yin Zhang, Yongchao Zhang, Junjie Wu, Jianyu Yang","doi":"10.1109/APSAR46974.2019.9048280","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048280","url":null,"abstract":"The resolution of bistatic SAR system is constrained by the signal bandwidth, distance, velocity and bistatic radar angle. The influence of topology structures and the strong coupling of echoes greatly limit the resolution of SAR images. And the problem of unbalanced two dimensional resolution brings difficulty and challenge to the target detection and recognition. Multi-static SAR can naturally form multiple pairs of bistatic SAR system and it fuses image information from multi-view by the design of topology structure to improve imaging resolution. To achieve optimal spatial resolution in all directions, the typical multi-static SAR geometric model is presented and the influence of topology structure on the two-dimensional resolution of bistatic and multi-static SAR is analyzed in this paper. Then, an equalization method to improve resolution for multi-static SAR is proposed. Finally, 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":"47 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":"126347513","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/APSAR46974.2019.9048571
Ying Zhang, W. Xiong, Xichao Dong, Cheng Hu, Chengxiang Liu, Yang Sun
In some case, the azimuth spectrum bandwidth is larger than the pulse repetition frequency (PRF), leading to a whole azimuth spectrum has been folded into multiple subsegments and aliased. Therefore, the traditional Doppler ambiguous integer estimation method cannot be used directly. In this paper, the influence of Doppler ambiguous integer on residual range migrations' slope is analyzed. Based on the slope, the Doppler ambiguous integer estimation method for moving targets with azimuth spectrum aliasing is given. From the simulation results, the Doppler ambiguous integer can be estimated accurately by proposed method.
{"title":"Range migration-based Doppler ambiguous integer estimation for moving targets with azimuth spectrum aliasing","authors":"Ying Zhang, W. Xiong, Xichao Dong, Cheng Hu, Chengxiang Liu, Yang Sun","doi":"10.1109/APSAR46974.2019.9048571","DOIUrl":"https://doi.org/10.1109/APSAR46974.2019.9048571","url":null,"abstract":"In some case, the azimuth spectrum bandwidth is larger than the pulse repetition frequency (PRF), leading to a whole azimuth spectrum has been folded into multiple subsegments and aliased. Therefore, the traditional Doppler ambiguous integer estimation method cannot be used directly. In this paper, the influence of Doppler ambiguous integer on residual range migrations' slope is analyzed. Based on the slope, the Doppler ambiguous integer estimation method for moving targets with azimuth spectrum aliasing is given. From the simulation results, the Doppler ambiguous integer can be estimated accurately by proposed method.","PeriodicalId":377019,"journal":{"name":"2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)","volume":"14 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":"126434170","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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