Pub Date : 2004-04-26DOI: 10.1109/NRC.2004.1316422
M. Martorella, F. Berizzi, S. Bruscoli
One of the most critical steps of ISAR image processing is the motion compensation, also known as ISAR image focusing. For non-cooperative targets and especially when external data are not available, autofocusing techniques must be used. Among all the techniques developed for ISAR image autofocusing, the contrast based autofocusing technique has been recently proposed by the authors. One of the critical aspects of such a technique is represented by the solution of an optimisation problem. Because the image contrast is generally a multimodal function, classic optimisation methods do not achieve the best result. In this paper a new solution of the optimisation problem is given by means of genetic algorithms. Moreover, the model of the focusing point phase history is extended to a generic polynomial and the problem of defining the polynomial order is addressed and heuristically solved. The effectiveness of the algorithm improvements, due to both the use of genetic algorithms and to the signal model extension is tested by means of real data.
{"title":"Use of genetic algorithms for ISAR image autofocusing","authors":"M. Martorella, F. Berizzi, S. Bruscoli","doi":"10.1109/NRC.2004.1316422","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316422","url":null,"abstract":"One of the most critical steps of ISAR image processing is the motion compensation, also known as ISAR image focusing. For non-cooperative targets and especially when external data are not available, autofocusing techniques must be used. Among all the techniques developed for ISAR image autofocusing, the contrast based autofocusing technique has been recently proposed by the authors. One of the critical aspects of such a technique is represented by the solution of an optimisation problem. Because the image contrast is generally a multimodal function, classic optimisation methods do not achieve the best result. In this paper a new solution of the optimisation problem is given by means of genetic algorithms. Moreover, the model of the focusing point phase history is extended to a generic polynomial and the problem of defining the polynomial order is addressed and heuristically solved. The effectiveness of the algorithm improvements, due to both the use of genetic algorithms and to the signal model extension is tested by means of real data.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123775749","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 : 2004-04-26DOI: 10.1109/NRC.2004.1316421
Junfeng Wang, D. Kasilingam, Xingzhao Liu, Zhixin Zhou
A new technique is developed for phase adjustment in ISAR imaging. The adjustment phase is found by iteratively solving an equation, which is derived by minimizing the entropy of the image. This technique can be used to estimate adjustment phases of any form. Moreover, the optimization method used in this technique is computationally more efficient than trial-and-error methods.
{"title":"ISAR minimum-entropy phase adjustment","authors":"Junfeng Wang, D. Kasilingam, Xingzhao Liu, Zhixin Zhou","doi":"10.1109/NRC.2004.1316421","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316421","url":null,"abstract":"A new technique is developed for phase adjustment in ISAR imaging. The adjustment phase is found by iteratively solving an equation, which is derived by minimizing the entropy of the image. This technique can be used to estimate adjustment phases of any form. Moreover, the optimization method used in this technique is computationally more efficient than trial-and-error methods.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116508012","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 : 2004-04-26DOI: 10.1109/NRC.2004.1316406
Daoying Ma, A. Zhang
Detecting the activities and predicting the tendencies of large groups of targets in wide battlefields are critical inputs to formulating sound military decisions. Modern airborne radar sensors can provide wide-area surveillance coverage of battlefield ground activities. When obscured by terrain or other factors, some objects may only be detectable at intervals, generating intermittent radar data and creating difficulties for tracking groups over time. We present an algorithm, termed CoreTracking, which dynamically groups individual targets into clusters and tracks the clusters over time. Most traditional clustering techniques are static-object-oriented. We propose a "core member" concept to support dynamic-object-oriented clustering and to mitigate the effects of data intermittence. Observing the movement of the core cluster members, we can track the clusters across frames and predict their future movements. The performance and results of applying the CoreTracking algorithm to CASTFOREM data sets is also presented.
{"title":"CoreTracking: an efficient approach to clustering moving targets and tracking clusters","authors":"Daoying Ma, A. Zhang","doi":"10.1109/NRC.2004.1316406","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316406","url":null,"abstract":"Detecting the activities and predicting the tendencies of large groups of targets in wide battlefields are critical inputs to formulating sound military decisions. Modern airborne radar sensors can provide wide-area surveillance coverage of battlefield ground activities. When obscured by terrain or other factors, some objects may only be detectable at intervals, generating intermittent radar data and creating difficulties for tracking groups over time. We present an algorithm, termed CoreTracking, which dynamically groups individual targets into clusters and tracks the clusters over time. Most traditional clustering techniques are static-object-oriented. We propose a \"core member\" concept to support dynamic-object-oriented clustering and to mitigate the effects of data intermittence. Observing the movement of the core cluster members, we can track the clusters across frames and predict their future movements. The performance and results of applying the CoreTracking algorithm to CASTFOREM data sets is also presented.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127051136","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 : 2004-04-26DOI: 10.1109/NRC.2004.1316468
J. Ferrante
A Kalman filter-based approach for fusing track data from two separate phased array radar sensors is developed and applied to a select ICBM case to demonstrate the potential enhancement of position and velocity estimates over a single radar. When compared to a theoretical assessment based on steady state filter performance, the Kalman filter approach yielded performance enhancements within 7% of theoretical prediction. The theoretical assessment indicated a 33% improvement in position accuracy and a 29% improvement in velocity accuracy for an assumed bias error in both radars. The simulation yielded a 29% improvement in position accuracy and a 22% improvement in velocity accuracy with the same bias assumption. The improvement was computed relative to the radar with twice the beamwidth and the same sensitivity as the second "fused" radar. The two radars were assumed to be collocated at the terminal area of ICBM flight.
{"title":"A Kalman filter-based radar track data fusion algorithm applied to a select ICBM case","authors":"J. Ferrante","doi":"10.1109/NRC.2004.1316468","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316468","url":null,"abstract":"A Kalman filter-based approach for fusing track data from two separate phased array radar sensors is developed and applied to a select ICBM case to demonstrate the potential enhancement of position and velocity estimates over a single radar. When compared to a theoretical assessment based on steady state filter performance, the Kalman filter approach yielded performance enhancements within 7% of theoretical prediction. The theoretical assessment indicated a 33% improvement in position accuracy and a 29% improvement in velocity accuracy for an assumed bias error in both radars. The simulation yielded a 29% improvement in position accuracy and a 22% improvement in velocity accuracy with the same bias assumption. The improvement was computed relative to the radar with twice the beamwidth and the same sensitivity as the second \"fused\" radar. The two radars were assumed to be collocated at the terminal area of ICBM flight.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127142213","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 : 2004-04-26DOI: 10.1109/NRC.2004.1316497
Guohua Wei, Siliang Wu, E. Mao
A vector miss distance estimation algorithm based on source localization is presented. A small antenna array is used for measuring the movement of a target. Phase differences among antennas and range from the target to the origin can be estimated by some modern spectral analysis method, such as ESPRIT or MUSIC. A closed-form source location estimate is given by the solution of a set of linear equations constructed from the estimates of phase differences and range. Then, by utilizing all source locations estimated from different samples, another set of linear equations is formed and unknown vector miss distance parameters can be estimated. Simulation results are provided to demonstrate the effectiveness and feasibility of the proposed method.
{"title":"Estimation of vector miss distance based on source localization","authors":"Guohua Wei, Siliang Wu, E. Mao","doi":"10.1109/NRC.2004.1316497","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316497","url":null,"abstract":"A vector miss distance estimation algorithm based on source localization is presented. A small antenna array is used for measuring the movement of a target. Phase differences among antennas and range from the target to the origin can be estimated by some modern spectral analysis method, such as ESPRIT or MUSIC. A closed-form source location estimate is given by the solution of a set of linear equations constructed from the estimates of phase differences and range. Then, by utilizing all source locations estimated from different samples, another set of linear equations is formed and unknown vector miss distance parameters can be estimated. Simulation results are provided to demonstrate the effectiveness and feasibility of the proposed method.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124160318","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 : 2004-04-26DOI: 10.1109/NRC.2004.1316460
A. Nelander
Terrain scattered interference mitigation methods for airborne radar have been studied and deconvolution methods for interference suppression have been proposed. This paper describes an analysis of the terrain scattered interference mitigation performance for different conditions and limitations. The direct path signal must be accurately estimated without strong multipath errors. A time-limited impulse response is required to avoid too much suppression of target signals. Small relative Doppler shift errors are required between the direct path and the terrain scattered paths. Several strong jamming signal sources cannot be resolved and suppressed. Receiver blocking gives errors in the impulse response estimate. Clutter signals must be suppressed for accurate impulse responses. Numerical stability must be ensured in the inverse filtering and deconvolution operations.
{"title":"Analysis of terrain scattered interference-mitigation","authors":"A. Nelander","doi":"10.1109/NRC.2004.1316460","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316460","url":null,"abstract":"Terrain scattered interference mitigation methods for airborne radar have been studied and deconvolution methods for interference suppression have been proposed. This paper describes an analysis of the terrain scattered interference mitigation performance for different conditions and limitations. The direct path signal must be accurately estimated without strong multipath errors. A time-limited impulse response is required to avoid too much suppression of target signals. Small relative Doppler shift errors are required between the direct path and the terrain scattered paths. Several strong jamming signal sources cannot be resolved and suppressed. Receiver blocking gives errors in the impulse response estimate. Clutter signals must be suppressed for accurate impulse responses. Numerical stability must be ensured in the inverse filtering and deconvolution operations.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128753850","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 : 2004-04-26DOI: 10.1109/NRC.2004.1316386
H. Kazemi, J. Hacker, H. Xin, M. Grace, B. Norvell, K. Higgins, M. Gilbert
The choice of InP HEMT technology is discussed for a highly efficient integrated T/R module. The module includes a receive path comprising of a low noise amplifier, phase shifter and amplifier consuming only 5 mW of DC power at X-band. The transmit path combines phase shifters and amplifiers to provide 10 mW of power per module at an efficiency of 50%. This is achieved by increasing the cut-off frequency of InP HEMT devices and sacrificing their gain for lower DC power consumption. This provides both DC and RF performance criteria for the space based radar antenna design requirements. Future T/R module technologies are also discussed, based on the antimonide based material system, which have already shown a factor of 3-4 reduction in DC power consumption compared to InP HEMT technology.
{"title":"An ultra-low power integrated T/R module for space-based radar technology","authors":"H. Kazemi, J. Hacker, H. Xin, M. Grace, B. Norvell, K. Higgins, M. Gilbert","doi":"10.1109/NRC.2004.1316386","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316386","url":null,"abstract":"The choice of InP HEMT technology is discussed for a highly efficient integrated T/R module. The module includes a receive path comprising of a low noise amplifier, phase shifter and amplifier consuming only 5 mW of DC power at X-band. The transmit path combines phase shifters and amplifiers to provide 10 mW of power per module at an efficiency of 50%. This is achieved by increasing the cut-off frequency of InP HEMT devices and sacrificing their gain for lower DC power consumption. This provides both DC and RF performance criteria for the space based radar antenna design requirements. Future T/R module technologies are also discussed, based on the antimonide based material system, which have already shown a factor of 3-4 reduction in DC power consumption compared to InP HEMT technology.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130317241","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 : 2004-04-26DOI: 10.1109/NRC.2004.1316453
C. Morgan, S. Jaroszewski, P. Mountcastle
We simulate the performance of existing and planned tactical GMTI (ground moving target indicator) systems using data cubes derived from high-fidelity interferometric SAR measurements, to assess the utility of these GMTI systems for an auxiliary terrain height estimation function. The two systems are current and next generation GMTI radars with linear and planar arrays, respectively, that could be mounted on a manned aircraft or a large UAV. In order to achieve the vertical element separation required for interferometric terrain height estimation, the antenna array in the first case must be pitched up relative to the horizontal position that is ordinarily used for DPCA or STAP clutter suppression. The purpose of the study is to determine whether useable terrain elevation maps can be generated by interferometric techniques within the operational constraints of these systems. Such elevation map data, obtained using a GMTI radar, would be valuable to knowledge-aided algorithms which rely on precise three-dimensional registration of radar data with terrain or road databases.
{"title":"Terrain height estimation using GMTI radar","authors":"C. Morgan, S. Jaroszewski, P. Mountcastle","doi":"10.1109/NRC.2004.1316453","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316453","url":null,"abstract":"We simulate the performance of existing and planned tactical GMTI (ground moving target indicator) systems using data cubes derived from high-fidelity interferometric SAR measurements, to assess the utility of these GMTI systems for an auxiliary terrain height estimation function. The two systems are current and next generation GMTI radars with linear and planar arrays, respectively, that could be mounted on a manned aircraft or a large UAV. In order to achieve the vertical element separation required for interferometric terrain height estimation, the antenna array in the first case must be pitched up relative to the horizontal position that is ordinarily used for DPCA or STAP clutter suppression. The purpose of the study is to determine whether useable terrain elevation maps can be generated by interferometric techniques within the operational constraints of these systems. Such elevation map data, obtained using a GMTI radar, would be valuable to knowledge-aided algorithms which rely on precise three-dimensional registration of radar data with terrain or road databases.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131565351","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 : 2004-04-26DOI: 10.1109/NRC.2004.1316459
S. Pillai, J. Guerci, S. R. Pillai
The sample support problem in space-time adaptive processing (STAP) arises from the requirement to adapt to a changing interference environment where the available wide-sense-stationary sample support is severely limited for direct implementation of adaptive algorithms. In this paper we outline several approaches to address the sample support problem by utilizing efficient covariance matrix tapering (CMT) methods to retain the a-priori known structure of the covariance matrix. By combining efficient tapering approaches along with terrain knowledge based STAP and other preprocessing schemes such as subarray - subpulse, relaxed projection method, it is possible to reduce the data samples required in a nonstationary environment and consequently achieve superior target detection. In addition, the application of Khatri-Rao product to the data domain implementation of CMT is also introduced thus expanding the class of robust algorithms for real-time STAP implementation.
{"title":"Efficient tapering methods for STAP","authors":"S. Pillai, J. Guerci, S. R. Pillai","doi":"10.1109/NRC.2004.1316459","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316459","url":null,"abstract":"The sample support problem in space-time adaptive processing (STAP) arises from the requirement to adapt to a changing interference environment where the available wide-sense-stationary sample support is severely limited for direct implementation of adaptive algorithms. In this paper we outline several approaches to address the sample support problem by utilizing efficient covariance matrix tapering (CMT) methods to retain the a-priori known structure of the covariance matrix. By combining efficient tapering approaches along with terrain knowledge based STAP and other preprocessing schemes such as subarray - subpulse, relaxed projection method, it is possible to reduce the data samples required in a nonstationary environment and consequently achieve superior target detection. In addition, the application of Khatri-Rao product to the data domain implementation of CMT is also introduced thus expanding the class of robust algorithms for real-time STAP implementation.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128185495","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 : 2004-04-26DOI: 10.1109/NRC.2004.1316443
David A. Garrenl, J. S. Goldsteinl, D.R. Obuchon, Robert R. Greene, J. A. North
Recent analysis has resulted in an innovative technique for forming synthetic aperture radar (SAR) images without the multipath ghost artifacts that arise in traditional methods. This technique separates direct-scatter echoes in an image from echoes that are the result of multipath, and then maps each set of reflections to a metrically correct image space. Current processing schemes place the multipath echoes at incorrect (i.e., ghost) locations due to fundamental assumptions implicit in conventional array processing. Two desired results are achieved by use of this new image reconstruction algorithm for multipath scattering (IRAMS). First, the intensities or the ghost returns are reduced in the primary image space, thereby improving the relationship between the image pattern and the physical distribution of the scatterers. Second, a higher dimensional image space that enhances the intensities of the multipath echoes is created which possesses characteristic information about the scene being imaged. These auxiliary "delay" image planes offer the potential or dramatically improving target detection and identification capabilities. This paper develops a robust IRAMS implementation that is based upon the cross-range drift in conventional SAR imagery of the multipath scattering events with respect to changes in the relative aspect angle. The resulting analysis is validated via simulated frequency response data that includes the effects of multipath scattering.
{"title":"SAR image formation algorithm with multipath reflectivity estimation","authors":"David A. Garrenl, J. S. Goldsteinl, D.R. Obuchon, Robert R. Greene, J. A. North","doi":"10.1109/NRC.2004.1316443","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316443","url":null,"abstract":"Recent analysis has resulted in an innovative technique for forming synthetic aperture radar (SAR) images without the multipath ghost artifacts that arise in traditional methods. This technique separates direct-scatter echoes in an image from echoes that are the result of multipath, and then maps each set of reflections to a metrically correct image space. Current processing schemes place the multipath echoes at incorrect (i.e., ghost) locations due to fundamental assumptions implicit in conventional array processing. Two desired results are achieved by use of this new image reconstruction algorithm for multipath scattering (IRAMS). First, the intensities or the ghost returns are reduced in the primary image space, thereby improving the relationship between the image pattern and the physical distribution of the scatterers. Second, a higher dimensional image space that enhances the intensities of the multipath echoes is created which possesses characteristic information about the scene being imaged. These auxiliary \"delay\" image planes offer the potential or dramatically improving target detection and identification capabilities. This paper develops a robust IRAMS implementation that is based upon the cross-range drift in conventional SAR imagery of the multipath scattering events with respect to changes in the relative aspect angle. The resulting analysis is validated via simulated frequency response data that includes the effects of multipath scattering.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133884098","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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