Pub Date : 2004-04-26DOI: 10.1109/NRC.2004.1316456
G. Schrader
The KASSPER project is a Defense Advanced Research Projects Agency (DARPA) program which has the goal of improving the performance of ground moving target indicator (GMTI) radar systems by incorporating external sources of knowledge into the signal processing chain. The KASSPER real-time signal processing architecture is a radar system scheduling and signal processing framework that is being developed at Massachusetts Institute of Technology Lincoln Laboratory (MIT LL). This paper discusses the design of the architecture, knowledge handling issues. resource scheduling issues, the current state of the prototype implementation of the framework, and the current state of the project's real-time processor testbed.
{"title":"The knowledge aided sensor signal processing and expert reasoning (KASSPER) real-time signal processing architecture [radar signal processing]","authors":"G. Schrader","doi":"10.1109/NRC.2004.1316456","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316456","url":null,"abstract":"The KASSPER project is a Defense Advanced Research Projects Agency (DARPA) program which has the goal of improving the performance of ground moving target indicator (GMTI) radar systems by incorporating external sources of knowledge into the signal processing chain. The KASSPER real-time signal processing architecture is a radar system scheduling and signal processing framework that is being developed at Massachusetts Institute of Technology Lincoln Laboratory (MIT LL). This paper discusses the design of the architecture, knowledge handling issues. resource scheduling issues, the current state of the prototype implementation of the framework, and the current state of the project's real-time processor testbed.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129876994","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.2004.1316447
S. Blunt, K. Gerlach, J. Heyer
The radar detection of targets in the presence of sea clutter has historically relied heavily upon the radial velocity of targets with respect to the radar platform, either by estimating the relative target Dopplers (such as for STAP) or by examining the path which targets traverse from scan to scan. However, for targets with little or no radial velocity component, it can become quite difficult to differentiate targets from the surrounding sea clutter. The paper addresses the detection of slow-moving targets in sea clutter and develops an approach for the non-coherent detection of such targets when high range resolution is available.
{"title":"Non-coherent detection of slow-moving targets in high-resolution sea clutter","authors":"S. Blunt, K. Gerlach, J. Heyer","doi":"10.1109/NRC.2004.1316447","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316447","url":null,"abstract":"The radar detection of targets in the presence of sea clutter has historically relied heavily upon the radial velocity of targets with respect to the radar platform, either by estimating the relative target Dopplers (such as for STAP) or by examining the path which targets traverse from scan to scan. However, for targets with little or no radial velocity component, it can become quite difficult to differentiate targets from the surrounding sea clutter. The paper addresses the detection of slow-moving targets in sea clutter and develops an approach for the non-coherent detection of such targets when high range resolution is available.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123094583","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.2004.1316399
S. Miranda, C. Baker, K. Woodbridge, H. Griffiths
Scheduling is an important sub-problem of radar resource management as there is a strong correlation between how tasks should be carried out and the time available to perform them. The paper compares two scheduling algorithms presented in the literature to investigate whether there are significant differences in their performance related to the allocation of radar time resources. We have developed a radar model applying a modular architecture to use the same operating and environment conditions in the analysis. The results suggest that, apart from minor differences, the algorithms provide similar performance.
{"title":"Phased array radar resource management: a comparison of scheduling algorithms","authors":"S. Miranda, C. Baker, K. Woodbridge, H. Griffiths","doi":"10.1109/NRC.2004.1316399","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316399","url":null,"abstract":"Scheduling is an important sub-problem of radar resource management as there is a strong correlation between how tasks should be carried out and the time available to perform them. The paper compares two scheduling algorithms presented in the literature to investigate whether there are significant differences in their performance related to the allocation of radar time resources. We have developed a radar model applying a modular architecture to use the same operating and environment conditions in the analysis. The results suggest that, apart from minor differences, the algorithms provide similar performance.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116204500","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.2004.1316435
J. Bergin, C. M. Teixeira, P. Techau
Synthetic aperture radar (SAR) exploits very high spatial resolution via temporal integration and own-ship motion to reduce the background clutter power in a given resolution cell to allow detection of non-moving targets. Ground moving target indicator (GMTI) radar, on the other hand, employs much lower resolution processing, but exploits the physical aperture and relative differences in the space-time response between moving targets and clutter for detection. Therefore, SAR and GMTl represent two different temporal processing resolution scales which have typically been optimized and demonstrated independently to work well for detecting either stationary (in the case of SAR) or exo-clutter (in the case of GMTI) targets. Based on this multi-resolution interpretation of airborne radar data processing, there appears to be an opportunity to develop detection techniques that attempt to optimize the signal processing resolution scale (e.g., length of temporal integration) to match the dynamics of a target of interest. The paper investigates signal processing techniques that exploit long CPIs (coherent processing intervals) to improve the detection performance of GMTl radar.
{"title":"Multi-resolution signal processing techniques for airborne radar","authors":"J. Bergin, C. M. Teixeira, P. Techau","doi":"10.1109/NRC.2004.1316435","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316435","url":null,"abstract":"Synthetic aperture radar (SAR) exploits very high spatial resolution via temporal integration and own-ship motion to reduce the background clutter power in a given resolution cell to allow detection of non-moving targets. Ground moving target indicator (GMTI) radar, on the other hand, employs much lower resolution processing, but exploits the physical aperture and relative differences in the space-time response between moving targets and clutter for detection. Therefore, SAR and GMTl represent two different temporal processing resolution scales which have typically been optimized and demonstrated independently to work well for detecting either stationary (in the case of SAR) or exo-clutter (in the case of GMTI) targets. Based on this multi-resolution interpretation of airborne radar data processing, there appears to be an opportunity to develop detection techniques that attempt to optimize the signal processing resolution scale (e.g., length of temporal integration) to match the dynamics of a target of interest. The paper investigates signal processing techniques that exploit long CPIs (coherent processing intervals) to improve the detection performance of GMTl radar.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131265900","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.2004.1316415
M. Conn, F. Koenig, G. Goldman, E. Adler
A multifunction, single platform RF sensor capable of performing target acquisition and tracking, combat identification, high data rate communications, and active protection is of interest to the USA army. The sensor ultimately must tie affordable and the size minimized to meet the demands of a rapidly deployable force. To address these needs, the Army Research Laboratory has built and tested a multifunction radar test bed capable of performing multiple tasks simultaneously at K/sub a/-band. The system has integrated high-end RF components together with commercial-off-the-shelf (COTS) signal processing technology. Key elements of the test bed are a commercial direct digital synthesizer (DDS) for adaptable waveform generation, multiple COTS field programmable gate array (FPGA) processors for real-time data acquisition and signal processing, a COTS FPGA based multi-port input/output (I/O) board programmed for radar timing and control, and an electronically scanned antenna (ESA) based upon a Rotman lens beam-former with active elements for multi-beam generation. The radar is capable of transmitting and receiving two simultaneous and independent beams in azimuth with up to 3 GHz of bandwidth and up to 8 watts of average power. The current configuration uses one beam for a radar target acquisition function and the other for a high data rate communication channel. The emphasis of this paper is on the radar's waveform generation and signal processing capability.
{"title":"Waveform generation and signal processing for a multifunction radar system","authors":"M. Conn, F. Koenig, G. Goldman, E. Adler","doi":"10.1109/NRC.2004.1316415","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316415","url":null,"abstract":"A multifunction, single platform RF sensor capable of performing target acquisition and tracking, combat identification, high data rate communications, and active protection is of interest to the USA army. The sensor ultimately must tie affordable and the size minimized to meet the demands of a rapidly deployable force. To address these needs, the Army Research Laboratory has built and tested a multifunction radar test bed capable of performing multiple tasks simultaneously at K/sub a/-band. The system has integrated high-end RF components together with commercial-off-the-shelf (COTS) signal processing technology. Key elements of the test bed are a commercial direct digital synthesizer (DDS) for adaptable waveform generation, multiple COTS field programmable gate array (FPGA) processors for real-time data acquisition and signal processing, a COTS FPGA based multi-port input/output (I/O) board programmed for radar timing and control, and an electronically scanned antenna (ESA) based upon a Rotman lens beam-former with active elements for multi-beam generation. The radar is capable of transmitting and receiving two simultaneous and independent beams in azimuth with up to 3 GHz of bandwidth and up to 8 watts of average power. The current configuration uses one beam for a radar target acquisition function and the other for a high data rate communication channel. The emphasis of this paper is on the radar's waveform generation and signal processing capability.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132602409","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":"103 1","pages":"0"},"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.2004.1316443
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":"53 1","pages":"0"},"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}
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":"127 1","pages":"0"},"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.2004.1316463
A. Ephrath, B. Vucetic
{"title":"4.6 Applications of space-time techniques in radar systems","authors":"A. Ephrath, B. Vucetic","doi":"10.1109/NRC.2004.1316463","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316463","url":null,"abstract":"","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116061398","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.2004.1316471
S. Grève, F. Lapierre, Jacques. Verly, F. Lapierre, Jacques. Verly
We address the problem of detecting slow moving targets from a moving radar system using space-time adaptive processing (STAP) techniques. Optimum interference rejection is known to require the estimation and the subsequent inversion of an interference-plus-noise covariance matrix. To reduce the number of training samples involved in the estimation and the computational cost inherent to the inversion, many suboptimum STAP techniques have been proposed. Earlier attempts at unifying these techniques had a limited scope. In this paper, we propose a new canonical framework that unifies all of the STAP methods we are aware of. This framework can also be generalized to include the estimation of the covariance matrix and the compensation of the range dependence; it applies to monostatic and bistatic configurations. We also propose a new decomposition of the CSNR performance metric that can be used to understand the performance degradation specifically due to the use of a suboptimum method.
{"title":"Canonical framework for describing suboptimum radar space-time adaptive processing (STAP) techniques","authors":"S. Grève, F. Lapierre, Jacques. Verly, F. Lapierre, Jacques. Verly","doi":"10.1109/NRC.2004.1316471","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316471","url":null,"abstract":"We address the problem of detecting slow moving targets from a moving radar system using space-time adaptive processing (STAP) techniques. Optimum interference rejection is known to require the estimation and the subsequent inversion of an interference-plus-noise covariance matrix. To reduce the number of training samples involved in the estimation and the computational cost inherent to the inversion, many suboptimum STAP techniques have been proposed. Earlier attempts at unifying these techniques had a limited scope. In this paper, we propose a new canonical framework that unifies all of the STAP methods we are aware of. This framework can also be generalized to include the estimation of the covariance matrix and the compensation of the range dependence; it applies to monostatic and bistatic configurations. We also propose a new decomposition of the CSNR performance metric that can be used to understand the performance degradation specifically due to the use of a suboptimum method.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116174032","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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