W. M. Aubry, R. Bonneau, R. Brown, E. D. Lynch, M. Wicks, R. Schneible, A. George, M. Krumme
This paper develops an airborne sensor concept to detect and image shallow-buried targets with a focus on the remote sensing of landmines. Our ongoing ground-based bistatic ground-penetrating radar (GPR) experiments have demonstrated deep penetration and subwavelength resolution. Simulation software (ground penetrating radar processing-GPRP) was developed and validated using experimental results. Extrapolation of the experimental results to higher frequencies using the simulation software indicates the ability to provide high-quality images of shallow-buried targets.
{"title":"Airborne sensor concept to image shallow-buried targets","authors":"W. M. Aubry, R. Bonneau, R. Brown, E. D. Lynch, M. Wicks, R. Schneible, A. George, M. Krumme","doi":"10.1109/NRC.2002.999724","DOIUrl":"https://doi.org/10.1109/NRC.2002.999724","url":null,"abstract":"This paper develops an airborne sensor concept to detect and image shallow-buried targets with a focus on the remote sensing of landmines. Our ongoing ground-based bistatic ground-penetrating radar (GPR) experiments have demonstrated deep penetration and subwavelength resolution. Simulation software (ground penetrating radar processing-GPRP) was developed and validated using experimental results. Extrapolation of the experimental results to higher frequencies using the simulation software indicates the ability to provide high-quality images of shallow-buried targets.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123304272","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}
Burst-mode data is obtained when a SAR system is operated in ScanSAR mode. First, a detailed description of the characteristics of the received burst-mode data is given. We then investigate the properties of the short IFFT (SIFFT) burst-mode processing algorithm and its input and output target space. A survey on the arithmetic of the SIFFT algorithm using the inverse momentary Fourier transform (IMFT) and the mixed-radix IFFT algorithms is given.
{"title":"On the properties and efficiency of the SIFFT SAR processing algorithm","authors":"S. Albrecht","doi":"10.1109/NRC.2002.999717","DOIUrl":"https://doi.org/10.1109/NRC.2002.999717","url":null,"abstract":"Burst-mode data is obtained when a SAR system is operated in ScanSAR mode. First, a detailed description of the characteristics of the received burst-mode data is given. We then investigate the properties of the short IFFT (SIFFT) burst-mode processing algorithm and its input and output target space. A survey on the arithmetic of the SIFFT algorithm using the inverse momentary Fourier transform (IMFT) and the mixed-radix IFFT algorithms is given.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122039198","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 development of radar polarimetry and radar interferometry is advancing rapidly. The textural fine structure, target orientation, system metrics and material constituents can be recovered with radar polarimetry; while with radar interferometry, the elevation structure of a target can be explored. Polarimetric synthetic aperture radar interferometric (Pol-InSAR) is interferometry between all possible polarization channels at each end of the baseline. Using polarimetric interferometry, the combination of the final structure properties and the spatial information of targets can be implemented. In this paper, we investigate the application of these three approaches to Earth terrain classification with results from the evaluation of fully polarimetric interferometric SIR-C/X-SAR data. The potential of Pol-InSAR for land cover classification has been demonstrated.
{"title":"Application of polarimetric synthetic aperture radar interferometry for land cover classification","authors":"Yang Zhen, Y. Ruliang","doi":"10.1109/NRC.2002.999761","DOIUrl":"https://doi.org/10.1109/NRC.2002.999761","url":null,"abstract":"The development of radar polarimetry and radar interferometry is advancing rapidly. The textural fine structure, target orientation, system metrics and material constituents can be recovered with radar polarimetry; while with radar interferometry, the elevation structure of a target can be explored. Polarimetric synthetic aperture radar interferometric (Pol-InSAR) is interferometry between all possible polarization channels at each end of the baseline. Using polarimetric interferometry, the combination of the final structure properties and the spatial information of targets can be implemented. In this paper, we investigate the application of these three approaches to Earth terrain classification with results from the evaluation of fully polarimetric interferometric SIR-C/X-SAR data. The potential of Pol-InSAR for land cover classification has been demonstrated.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125296942","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}
In this paper we discuss spatial superresolution methods applied to the received data of a conformal array antenna. The "sequential MUSIC" and the "sequential alternating projection" methods are derived. Besides the angles of arrival we estimate additionally the polarization states of the received signals. The theoretical derivations are verified and experimental results are shown.
{"title":"Superresolution with conformal broadband antenna arrays","authors":"J. Worms","doi":"10.1109/NRC.2002.999756","DOIUrl":"https://doi.org/10.1109/NRC.2002.999756","url":null,"abstract":"In this paper we discuss spatial superresolution methods applied to the received data of a conformal array antenna. The \"sequential MUSIC\" and the \"sequential alternating projection\" methods are derived. Besides the angles of arrival we estimate additionally the polarization states of the received signals. The theoretical derivations are verified and experimental results are shown.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121270451","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}
A new squint dependent formulation of the known reflectivity displacement method (RDM) for motion error extraction is presented. This new formulation extends RDM applicability under high squint angles with a negligible computational overload. The data obtained is suitable for high quality synthetic aperture radar (SAR) processing with motion compensation avoiding the use of expensive inertial navigation system (INS) and GPS systems for many applications.
{"title":"An improved RDM method specially useful for low cost SAR high squint processing","authors":"J. Crespo, J. Gutierrez","doi":"10.1109/NRC.2002.999718","DOIUrl":"https://doi.org/10.1109/NRC.2002.999718","url":null,"abstract":"A new squint dependent formulation of the known reflectivity displacement method (RDM) for motion error extraction is presented. This new formulation extends RDM applicability under high squint angles with a negligible computational overload. The data obtained is suitable for high quality synthetic aperture radar (SAR) processing with motion compensation avoiding the use of expensive inertial navigation system (INS) and GPS systems for many applications.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129653162","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}
This paper addresses the problem of clutter patch identification based on Markov random field (MRF) models. MRF has long been recognized by the image processing community to be an accurate model to describe a variety of image characteristics such as texture. Here, we use the MRF to model clutter patch characteristics, captured by a radar receiver or radar imagery equipment, due to the fact that clutter patches usually occur in connected regions. Furthermore, we assume that observations inside each clutter patch are homogenous, i.e., observations follow a single probability distribution. We use the Metropolis-Hasting algorithm and the reversible jump Markov chain algorithm to search for solutions based on the maximum a posteriori (MAP) criterion. Several examples are provided to illustrate the performance of our algorithm.
{"title":"Clutter patch identification based on Markov random field models","authors":"T. Kasetkasem, P. Varshney","doi":"10.1109/NRC.2002.999762","DOIUrl":"https://doi.org/10.1109/NRC.2002.999762","url":null,"abstract":"This paper addresses the problem of clutter patch identification based on Markov random field (MRF) models. MRF has long been recognized by the image processing community to be an accurate model to describe a variety of image characteristics such as texture. Here, we use the MRF to model clutter patch characteristics, captured by a radar receiver or radar imagery equipment, due to the fact that clutter patches usually occur in connected regions. Furthermore, we assume that observations inside each clutter patch are homogenous, i.e., observations follow a single probability distribution. We use the Metropolis-Hasting algorithm and the reversible jump Markov chain algorithm to search for solutions based on the maximum a posteriori (MAP) criterion. Several examples are provided to illustrate the performance of our algorithm.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127473798","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}
We address the problem of training data corruption in space-time adaptive processing (STAP) for ground moving target indication (GMTI) radar scenarios characterized by high densities of ground targets. A site-specific clutter simulation is used to demonstrate the impact that target signals in the training data have on STAP performance. Measured MCARM data results are presented that reveal similar performance trends as those observed in the simulations. A strategy for mitigating the deleterious effects of targets in the training data using a priori knowledge of the radar environment (e.g., locations of roads) to edit the training data is presented.
{"title":"GMTI STAP in target-rich environments: site-specific analysis","authors":"J. Bergin, P. Techau, W. Melvin, J. Guerci","doi":"10.1109/NRC.2002.999750","DOIUrl":"https://doi.org/10.1109/NRC.2002.999750","url":null,"abstract":"We address the problem of training data corruption in space-time adaptive processing (STAP) for ground moving target indication (GMTI) radar scenarios characterized by high densities of ground targets. A site-specific clutter simulation is used to demonstrate the impact that target signals in the training data have on STAP performance. Measured MCARM data results are presented that reveal similar performance trends as those observed in the simulations. A strategy for mitigating the deleterious effects of targets in the training data using a priori knowledge of the radar environment (e.g., locations of roads) to edit the training data is presented.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131399592","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}
We propose a multi-step procedure for constructing a lower confidence limit for the number of signals present. We derive the probability of a correct estimation, P(CE), and the least favorable configuration (LFC) for our procedure. Under LFC, the P(CE) attains its minimum over the parameter space of all eigenvalues. Therefore a minimum sample size can be determined in order to implement our procedure with a guaranteed probability requirement.
{"title":"A lower confidence limit for the number of signals","authors":"Pinyuen Chen, M. Wicks","doi":"10.1109/NRC.2002.999744","DOIUrl":"https://doi.org/10.1109/NRC.2002.999744","url":null,"abstract":"We propose a multi-step procedure for constructing a lower confidence limit for the number of signals present. We derive the probability of a correct estimation, P(CE), and the least favorable configuration (LFC) for our procedure. Under LFC, the P(CE) attains its minimum over the parameter space of all eigenvalues. Therefore a minimum sample size can be determined in order to implement our procedure with a guaranteed probability requirement.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133714617","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}
Critical issues associated with the application of multi-dimensional adaptive filtering including space-time adaptive processing (STAP) to real-world radar systems are considered. In particular, the design of transform domain localized techniques are examined from the perspective of receiver beam position and Doppler filter selection relative to mainlobe clutter as well as target returns. In particular, asymmetry in the selection of auxiliary beams and the effects of spatial tapering are shown to offer dramatic improvements in signal to interference ratio for targets with low Doppler.
{"title":"A new constrained joint-domain localized approach for airborne radars","authors":"B. Himed, M. Wicks, P. Zulch","doi":"10.1109/NRC.2002.999752","DOIUrl":"https://doi.org/10.1109/NRC.2002.999752","url":null,"abstract":"Critical issues associated with the application of multi-dimensional adaptive filtering including space-time adaptive processing (STAP) to real-world radar systems are considered. In particular, the design of transform domain localized techniques are examined from the perspective of receiver beam position and Doppler filter selection relative to mainlobe clutter as well as target returns. In particular, asymmetry in the selection of auxiliary beams and the effects of spatial tapering are shown to offer dramatic improvements in signal to interference ratio for targets with low Doppler.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114704281","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 sample support problem in space-time adaptive processing (STAP) applications arises from the requirement to adapt many spatial and temporal degrees-of-freedom (DOF) to a changing interference environment that includes clutter and jammers. Often, in heterogeneous overland strong clutter environments, the available wide sense stationary sample support is severely limited to preclude the direct implementation of the sample matrix inverse (SMI) approach. We outline an approach to address the sample support problem by utilizing projection methods - alternating projections or relaxed projection operators onto desired convex sets - to retain the a-priori known structure of the covariance matrix. Our initial analysis shows that by combining these approaches with eigen-based techniques, it is possible to reduce significantly the data samples required in non-stationary environment and consequently achieve superior target detection. In fact, multiplicative improvement in data reduction compared to direct eigen-based methods can be obtained at the expense of negligible loss in space-time aperture.
{"title":"Projection approach for STAP","authors":"S. Pillai, S. R. Pillai","doi":"10.1109/NRC.2002.999751","DOIUrl":"https://doi.org/10.1109/NRC.2002.999751","url":null,"abstract":"The sample support problem in space-time adaptive processing (STAP) applications arises from the requirement to adapt many spatial and temporal degrees-of-freedom (DOF) to a changing interference environment that includes clutter and jammers. Often, in heterogeneous overland strong clutter environments, the available wide sense stationary sample support is severely limited to preclude the direct implementation of the sample matrix inverse (SMI) approach. We outline an approach to address the sample support problem by utilizing projection methods - alternating projections or relaxed projection operators onto desired convex sets - to retain the a-priori known structure of the covariance matrix. Our initial analysis shows that by combining these approaches with eigen-based techniques, it is possible to reduce significantly the data samples required in non-stationary environment and consequently achieve superior target detection. In fact, multiplicative improvement in data reduction compared to direct eigen-based methods can be obtained at the expense of negligible loss in space-time aperture.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122597181","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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