Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059255
H. I. Ahmed, Q. Wan
In this paper, the completion of missing measurements in a squared distances matrix through Nystrom completion algorithm have been investigated. this missing occurred due to limitation of power when the sensors are deployed in a large area. The Nystrom algorithm has overcome the classical multidimensional scaling in a low and moderate signal to noise ratio, in addition it performed well as the number of missing entries increased. The plotted figures show admissible consequences for the proposed algorithm.
{"title":"Sources localization through matrix completion via Nystrom completion","authors":"H. I. Ahmed, Q. Wan","doi":"10.1109/RADAR.2016.8059255","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059255","url":null,"abstract":"In this paper, the completion of missing measurements in a squared distances matrix through Nystrom completion algorithm have been investigated. this missing occurred due to limitation of power when the sensors are deployed in a large area. The Nystrom algorithm has overcome the classical multidimensional scaling in a low and moderate signal to noise ratio, in addition it performed well as the number of missing entries increased. The plotted figures show admissible consequences for the proposed algorithm.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128839675","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 : 2016-10-01DOI: 10.1109/RADAR.2016.8059489
Yonghong Yao, Wei Song, Shaohua Ye
For airborne spotlight mode synthetic aperture radar (SAR) autofocusing, the residual range cell migration (RRCM) results in performance degradation. An improved inverse filtering (IF) autofocus approach based on the isolated strong point target is proposed in this paper. The new approach can simultaneously compensate both azimuth phase error and the two dimensional coupling phase error caused by the residual range migration. Therefor the bad effect caused by RRCM on autofocusing is eliminated, and the performance of inverse filtering autofocus algorithm is improved obviously. The results of real-measured data processing validate the effectiveness of the proposed method.
{"title":"An improved autofocus approach based on 2-D inverse filtering for airborne spotlight SAR","authors":"Yonghong Yao, Wei Song, Shaohua Ye","doi":"10.1109/RADAR.2016.8059489","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059489","url":null,"abstract":"For airborne spotlight mode synthetic aperture radar (SAR) autofocusing, the residual range cell migration (RRCM) results in performance degradation. An improved inverse filtering (IF) autofocus approach based on the isolated strong point target is proposed in this paper. The new approach can simultaneously compensate both azimuth phase error and the two dimensional coupling phase error caused by the residual range migration. Therefor the bad effect caused by RRCM on autofocusing is eliminated, and the performance of inverse filtering autofocus algorithm is improved obviously. The results of real-measured data processing validate the effectiveness of the proposed method.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128847378","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 : 2016-10-01DOI: 10.1109/RADAR.2016.8059188
Jiang Peng, Jianping Ou, Jun Zhang
To improve the anti-interference capability of high range resolution radar, the random hopping frequency signal is required. A waveform design method of random hopping frequency signal based on "S" curve is presented. Firstly, the random hopping frequency signal with low peak side lobe is obtained by optimization. Then the frequency distribution is analyzed and fitted by "S" curve. The ambiguity function of RHF signal based on different window functions is evaluated. The results show that the random hopping frequency signal has low peak sidelobe level, small mainlobe broadening, strong anti-interference capability and low implementation cost, which indicates its high practical value in real applications.
{"title":"The waveform design of random hopping frequency based on \"S\" curve","authors":"Jiang Peng, Jianping Ou, Jun Zhang","doi":"10.1109/RADAR.2016.8059188","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059188","url":null,"abstract":"To improve the anti-interference capability of high range resolution radar, the random hopping frequency signal is required. A waveform design method of random hopping frequency signal based on \"S\" curve is presented. Firstly, the random hopping frequency signal with low peak side lobe is obtained by optimization. Then the frequency distribution is analyzed and fitted by \"S\" curve. The ambiguity function of RHF signal based on different window functions is evaluated. The results show that the random hopping frequency signal has low peak sidelobe level, small mainlobe broadening, strong anti-interference capability and low implementation cost, which indicates its high practical value in real applications.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"391 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126745364","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 : 2016-10-01DOI: 10.1109/RADAR.2016.8059313
Chen-long Yu, Xiansi Tan, Fan Li
Search ability of long range early-warning phased array radar without indication information is studied in this paper, based on the background of near space hypersonic targets defense. Design principle and validation method of radar search parameters such as search screen, signal cycle and search frame period are deeply discussed in the case of near space work pattern, the shortest cross-screen distance and the minimum number of scans of radar are formulated based on the target motion state. Finally, radar detecting ability is analyzed through simulation, which shows that radar has the whole capacity to capture the target when it coming right against the face, while it should take the mode of TWS when it coming from behind the head space.
{"title":"Study on search performance of long range early-warning phased array radar","authors":"Chen-long Yu, Xiansi Tan, Fan Li","doi":"10.1109/RADAR.2016.8059313","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059313","url":null,"abstract":"Search ability of long range early-warning phased array radar without indication information is studied in this paper, based on the background of near space hypersonic targets defense. Design principle and validation method of radar search parameters such as search screen, signal cycle and search frame period are deeply discussed in the case of near space work pattern, the shortest cross-screen distance and the minimum number of scans of radar are formulated based on the target motion state. Finally, radar detecting ability is analyzed through simulation, which shows that radar has the whole capacity to capture the target when it coming right against the face, while it should take the mode of TWS when it coming from behind the head space.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"CE-31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126547486","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 : 2016-10-01DOI: 10.1109/RADAR.2016.8059438
Xiang Long, Xiang Hu, Li Shaodong, M. Xiaoyan
To recover the jointly sparse signal efficiently, a fast multiple orthogonal matching pursuit algorithm (FMOMP) is proposed in the paper. By choosing multiple indices per iteration, the FMOMP converges much faster and improves the computational efficiency over the existing OMPMMV algorithm. We also prove that FMOMP performs the exact recovery of any K row jointly sparse signal from the aspect of sensing matrix's restricted isometry property (RIP). Empirical experiments show that FMOMP is very efficient in recovering jointly sparse signal compared to the state of the art recovery algorithms.
{"title":"A fast multiple orthogonal matching pursuit algorithm for jointly sparse recovery","authors":"Xiang Long, Xiang Hu, Li Shaodong, M. Xiaoyan","doi":"10.1109/RADAR.2016.8059438","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059438","url":null,"abstract":"To recover the jointly sparse signal efficiently, a fast multiple orthogonal matching pursuit algorithm (FMOMP) is proposed in the paper. By choosing multiple indices per iteration, the FMOMP converges much faster and improves the computational efficiency over the existing OMPMMV algorithm. We also prove that FMOMP performs the exact recovery of any K row jointly sparse signal from the aspect of sensing matrix's restricted isometry property (RIP). Empirical experiments show that FMOMP is very efficient in recovering jointly sparse signal compared to the state of the art recovery algorithms.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121622458","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 : 2016-10-01DOI: 10.1109/RADAR.2016.8059448
Yuxi Zhang, Junkai Wang, Yunneng Yuan
Migration Compensation can eliminate the influence of target movement during the long-time integration which can increase the detection probability of stealth aircraft in Pulse-Doppler (PD) Radar. Both frequency-domain correction and time-domain correction are common methods of migration compensation. In this paper, a digital signal processing platform which based on Field Programmable Gate Array (FPGA) is designed to implement the two ways of migration compensation. Also the details of implementation are described. At the end of the paper, the comparison of performance and resource consumption are presented. With the same sampling rate, the SNR gains of two methods are almost the same. However, frequency-domain correction consumes more internal calculation resource in FPGA while time-domain correction needs more external storage resource.
{"title":"Research and implement of migration compensation in PD radar based on FPGA","authors":"Yuxi Zhang, Junkai Wang, Yunneng Yuan","doi":"10.1109/RADAR.2016.8059448","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059448","url":null,"abstract":"Migration Compensation can eliminate the influence of target movement during the long-time integration which can increase the detection probability of stealth aircraft in Pulse-Doppler (PD) Radar. Both frequency-domain correction and time-domain correction are common methods of migration compensation. In this paper, a digital signal processing platform which based on Field Programmable Gate Array (FPGA) is designed to implement the two ways of migration compensation. Also the details of implementation are described. At the end of the paper, the comparison of performance and resource consumption are presented. With the same sampling rate, the SNR gains of two methods are almost the same. However, frequency-domain correction consumes more internal calculation resource in FPGA while time-domain correction needs more external storage resource.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"4 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120978674","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 : 2016-10-01DOI: 10.1109/RADAR.2016.8059373
Yu Xing, Xiaoyong Du, W. Hu, Jian Wang
The Focal Underdetermined System Solver (FOCUSS) method is widely applied in the compressive sensing (CS) based high resolution range profile (HRRP) reconstruction. However, the parameter estimation of the scattering center type is not accurate enough. In this paper, an algorithm named by local reoptimization FOCUSS is presented to deal with such a case. After the traditional FOCUSS algorithm being applied, the estimated parameters of each extracted scattering center in a given range cell are modified by minimizing the construction residual upon each atom with different type of parameter. Finally, the numerical simulations show that the proposed method can effectively estimate the parameters of attributed scattering centers while the traditional FOCUSS algorithm fails, especially for the estimation of type parameter.
{"title":"High resolution range profile reconstruction based on local reoptimization FOCUSS algorithm","authors":"Yu Xing, Xiaoyong Du, W. Hu, Jian Wang","doi":"10.1109/RADAR.2016.8059373","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059373","url":null,"abstract":"The Focal Underdetermined System Solver (FOCUSS) method is widely applied in the compressive sensing (CS) based high resolution range profile (HRRP) reconstruction. However, the parameter estimation of the scattering center type is not accurate enough. In this paper, an algorithm named by local reoptimization FOCUSS is presented to deal with such a case. After the traditional FOCUSS algorithm being applied, the estimated parameters of each extracted scattering center in a given range cell are modified by minimizing the construction residual upon each atom with different type of parameter. Finally, the numerical simulations show that the proposed method can effectively estimate the parameters of attributed scattering centers while the traditional FOCUSS algorithm fails, especially for the estimation of type parameter.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"59 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121009885","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 : 2016-10-01DOI: 10.1109/RADAR.2016.8059256
A. Potapov, F. F. Lazko
This article gives a brief description of two widely used texture measures of SAR and UAVs images. They are gradients distribution or co-occurrence matrices and lacunarity. We also provide detailed outlines of mentioned above matrices calculation in order to introduce the way of texture features extraction. At the end of the article, we examine functional connection between the first texture feature and absolute value of offset.
{"title":"Gradients distribution matrices and lacunarity in the capacity of texture measures of SAR and UAVs images","authors":"A. Potapov, F. F. Lazko","doi":"10.1109/RADAR.2016.8059256","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059256","url":null,"abstract":"This article gives a brief description of two widely used texture measures of SAR and UAVs images. They are gradients distribution or co-occurrence matrices and lacunarity. We also provide detailed outlines of mentioned above matrices calculation in order to introduce the way of texture features extraction. At the end of the article, we examine functional connection between the first texture feature and absolute value of offset.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121695707","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 : 2016-10-01DOI: 10.1109/RADAR.2016.8059148
Di Xu, Gong Zhang, Zhenni Peng
To improve the parameter estimation performance of the compressed sensing(CS) theory based MIMO radar, a method of optimizing the sparse random array in CS-MIMO radar is proposed. Considering the difficulty of hardware implementation of the typically used measurement matrix such as Gaussian random matrix, in this paper, we exploit the inner connection between sparse random array and CS to study a new method of measurement matrix construction and make use of the randomness of the array elements to realize compressive measurement. The simulated annealing is applied to the sparse random array optimization in CS-MIMO radar in order to reduce the coherence of the equivalent sensing matrix and improve the parameter estimation performance by acting on the elements' positions of transmitting and receiving arrays. The simulation results verify the effectiveness of the proposed approach.
{"title":"Optimization design of CS-MIMO radar sparse random array","authors":"Di Xu, Gong Zhang, Zhenni Peng","doi":"10.1109/RADAR.2016.8059148","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059148","url":null,"abstract":"To improve the parameter estimation performance of the compressed sensing(CS) theory based MIMO radar, a method of optimizing the sparse random array in CS-MIMO radar is proposed. Considering the difficulty of hardware implementation of the typically used measurement matrix such as Gaussian random matrix, in this paper, we exploit the inner connection between sparse random array and CS to study a new method of measurement matrix construction and make use of the randomness of the array elements to realize compressive measurement. The simulated annealing is applied to the sparse random array optimization in CS-MIMO radar in order to reduce the coherence of the equivalent sensing matrix and improve the parameter estimation performance by acting on the elements' positions of transmitting and receiving arrays. The simulation results verify the effectiveness of the proposed approach.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122494843","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 : 2016-10-01DOI: 10.1109/RADAR.2016.8059250
Cunxu Li, Baixiao Chen, Minglei Yang
In this paper, a novel off-grid direction-of-arrival (DOA) estimation algorithm involving sparse recovery is proposed based on weighted subspace fitting, in which multiple snapshots are used and effects of off-grid DOA are taken into account. The DOA estimation problem is formulated as a binary cost function, then an iterative sparse recovery algorithm alternating resolved the unknown variables with weighted linorm approximation method is developed to estimate DOA accurately. The proposed algorithm obtains improved accuracy compared with the existing methods. Simulation results demonstrate that the proposed algorithm can estimate the DOA with high accuracy for correlated signals while maintaining a relatively low computational cost.
{"title":"A novel off-grid DOA estimation via weighted subspace fitting","authors":"Cunxu Li, Baixiao Chen, Minglei Yang","doi":"10.1109/RADAR.2016.8059250","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059250","url":null,"abstract":"In this paper, a novel off-grid direction-of-arrival (DOA) estimation algorithm involving sparse recovery is proposed based on weighted subspace fitting, in which multiple snapshots are used and effects of off-grid DOA are taken into account. The DOA estimation problem is formulated as a binary cost function, then an iterative sparse recovery algorithm alternating resolved the unknown variables with weighted linorm approximation method is developed to estimate DOA accurately. The proposed algorithm obtains improved accuracy compared with the existing methods. Simulation results demonstrate that the proposed algorithm can estimate the DOA with high accuracy for correlated signals while maintaining a relatively low computational cost.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"22 6S 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122809636","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：