The purpose of this work is to establish how a moving emitter, such as a jammer, can be localized by a passive receiver through the use of out-of-plane multipath signals reflected by the terrain. This is a novel localization technique that assumes no a priori knowledge of the location of the multipath sources. The emitter parameters of range, heading, velocity, and altitude are estimated by exploiting the correlation between the direct-path signal and the delayed and Doppler modulated signals. Based on an assumption that the bistatic clutter is fundamentally homogeneous, the maximum likelihood estimator is designed and found to have the structure of a time-varying FIR filter. The Cramer-Rao lower bounds are calculated and used to study the estimator performance. The proposed estimator is successfully demonstrated using field data collected at White Sands Missile Range during the DARPA/Navy Mountaintop program.
{"title":"3-D jammer localization using out-of-plane multipath","authors":"S. Coutts","doi":"10.1109/NRC.1998.678004","DOIUrl":"https://doi.org/10.1109/NRC.1998.678004","url":null,"abstract":"The purpose of this work is to establish how a moving emitter, such as a jammer, can be localized by a passive receiver through the use of out-of-plane multipath signals reflected by the terrain. This is a novel localization technique that assumes no a priori knowledge of the location of the multipath sources. The emitter parameters of range, heading, velocity, and altitude are estimated by exploiting the correlation between the direct-path signal and the delayed and Doppler modulated signals. Based on an assumption that the bistatic clutter is fundamentally homogeneous, the maximum likelihood estimator is designed and found to have the structure of a time-varying FIR filter. The Cramer-Rao lower bounds are calculated and used to study the estimator performance. The proposed estimator is successfully demonstrated using field data collected at White Sands Missile Range during the DARPA/Navy Mountaintop program.","PeriodicalId":432418,"journal":{"name":"Proceedings of the 1998 IEEE Radar Conference, RADARCON'98. Challenges in Radar Systems and Solutions (Cat. No.98CH36197)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124819216","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 introduces a new method of partially adaptive CFAR detection. The processor implements a novel sequence of orthogonal subspace projections to decompose the Wiener solution in terms of the cross-correlation observed at each stage. The detection performance is evaluated in the general framework of space-time adaptive processing. It is demonstrated that this new approach to partially adaptive CFAR detection outperforms the more complex eigen-analysis approaches using true pulse-Doppler radar data collected by the multichannel airborne radar measurements (MCARM) radar.
{"title":"A multistage STAP CFAR detection technique","authors":"J. S. Goldstein, I. Reed, P. Zulch, W. Melvin","doi":"10.1109/NRC.1998.677986","DOIUrl":"https://doi.org/10.1109/NRC.1998.677986","url":null,"abstract":"This paper introduces a new method of partially adaptive CFAR detection. The processor implements a novel sequence of orthogonal subspace projections to decompose the Wiener solution in terms of the cross-correlation observed at each stage. The detection performance is evaluated in the general framework of space-time adaptive processing. It is demonstrated that this new approach to partially adaptive CFAR detection outperforms the more complex eigen-analysis approaches using true pulse-Doppler radar data collected by the multichannel airborne radar measurements (MCARM) radar.","PeriodicalId":432418,"journal":{"name":"Proceedings of the 1998 IEEE Radar Conference, RADARCON'98. Challenges in Radar Systems and Solutions (Cat. No.98CH36197)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131574526","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 present a wavelet shrinkage method that yields high clutter suppression by using a best-tree wavelet packet analysis. An integrated automatic target recognition processor utilizing a wavelet packet transform and a shape extraction method is introduced to demonstrate the feasibility of using wavelet packet analysis for automatic target extraction from synthetic aperture radar (SAR) images. Two analysis procedures are processed independently and the two outputs from each process are combined to increase the detection performance. Experimental demonstrations of target extraction are also provided. The preliminary experiments show that target extraction using wavelet packet analysis has high detection performance as well as low false detection performance.
{"title":"Target extraction from clutter images using wavelet packet analysis","authors":"HyungJun Kim, P. Liang","doi":"10.1109/NRC.1998.678000","DOIUrl":"https://doi.org/10.1109/NRC.1998.678000","url":null,"abstract":"We present a wavelet shrinkage method that yields high clutter suppression by using a best-tree wavelet packet analysis. An integrated automatic target recognition processor utilizing a wavelet packet transform and a shape extraction method is introduced to demonstrate the feasibility of using wavelet packet analysis for automatic target extraction from synthetic aperture radar (SAR) images. Two analysis procedures are processed independently and the two outputs from each process are combined to increase the detection performance. Experimental demonstrations of target extraction are also provided. The preliminary experiments show that target extraction using wavelet packet analysis has high detection performance as well as low false detection performance.","PeriodicalId":432418,"journal":{"name":"Proceedings of the 1998 IEEE Radar Conference, RADARCON'98. Challenges in Radar Systems and Solutions (Cat. No.98CH36197)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132518193","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 present a new methodology for detecting moving objects based on the analysis of variance. This new detector is a generalization of feature based and optical-flow based techniques. Our algorithm is effective in enhancing the detection of range-spread/Doppler-spread targets and in suppressing background interference, with application to synthetic aperture radar and high resolution millimeter wave imaging sensors, in addition to optical and infrared cameras. The statistics necessary for implementation are estimated under both the null hypothesis and its alternative. The performance is demonstrated via analysis of measured data.
{"title":"A space-time adaptive detector for moving targets based on the analysis of variance","authors":"J. Cheung, G.J. Genello, M. Wicks","doi":"10.1109/NRC.1998.678018","DOIUrl":"https://doi.org/10.1109/NRC.1998.678018","url":null,"abstract":"We present a new methodology for detecting moving objects based on the analysis of variance. This new detector is a generalization of feature based and optical-flow based techniques. Our algorithm is effective in enhancing the detection of range-spread/Doppler-spread targets and in suppressing background interference, with application to synthetic aperture radar and high resolution millimeter wave imaging sensors, in addition to optical and infrared cameras. The statistics necessary for implementation are estimated under both the null hypothesis and its alternative. The performance is demonstrated via analysis of measured data.","PeriodicalId":432418,"journal":{"name":"Proceedings of the 1998 IEEE Radar Conference, RADARCON'98. Challenges in Radar Systems and Solutions (Cat. No.98CH36197)","volume":"6414 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126413935","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 present a new method for automatic target/object classification by using the optimum polarimetric radar signatures of the targets/objects of interest. The use of optimum polarimetric signatures for enhancing target recognition using synthetic aperture radar is explored. The polarization scattering matrix is used for the derivation of target signatures at arbitrary transmit and receive polarizations (arbitrary polarization inclination angles and ellipticity angles). Then an optimization criterion that minimizes the within class distance and maximizes the between class metrics is used for the derivation of optimum sets of polarimetric signatures. Then from sets of real fully polarimetric SAR imagery arbitrary polarization attributes are extracted. The performance of the automatic target detection and recognition algorithms using optimum sets of polarimetric signatures are derived and compared with those associated with the non-optimum signatures. The results show that noticeable improvements can be achieved by using the SAR signatures obtained via optimum transmits and receives over non-optimum signatures. This work indicates that by optimally adjusting the radar polarization-by using polarization filters-the target classification performance can be improved and targets that may not be easily separable can be separated.
{"title":"Enhanced target recognition using optimum polarimetric SAR signatures","authors":"F. Sadjadi","doi":"10.1109/NRC.1998.678017","DOIUrl":"https://doi.org/10.1109/NRC.1998.678017","url":null,"abstract":"We present a new method for automatic target/object classification by using the optimum polarimetric radar signatures of the targets/objects of interest. The use of optimum polarimetric signatures for enhancing target recognition using synthetic aperture radar is explored. The polarization scattering matrix is used for the derivation of target signatures at arbitrary transmit and receive polarizations (arbitrary polarization inclination angles and ellipticity angles). Then an optimization criterion that minimizes the within class distance and maximizes the between class metrics is used for the derivation of optimum sets of polarimetric signatures. Then from sets of real fully polarimetric SAR imagery arbitrary polarization attributes are extracted. The performance of the automatic target detection and recognition algorithms using optimum sets of polarimetric signatures are derived and compared with those associated with the non-optimum signatures. The results show that noticeable improvements can be achieved by using the SAR signatures obtained via optimum transmits and receives over non-optimum signatures. This work indicates that by optimally adjusting the radar polarization-by using polarization filters-the target classification performance can be improved and targets that may not be easily separable can be separated.","PeriodicalId":432418,"journal":{"name":"Proceedings of the 1998 IEEE Radar Conference, RADARCON'98. Challenges in Radar Systems and Solutions (Cat. No.98CH36197)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126218797","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 describes a compression technique under development at Sandia National Laboratories for the compression of complex synthetic aperture radar (SAR) imagery at very low overall bit rates. The methods involved combine several elements of existing and new lossy and lossless compression schemes in order to achieve an overall compression ratio of large SAR scenes of at least 50:1, while maintaining reasonable image quality. It is assumed that the end user will be primarily interested in specific regions of interest within the image (called "chips"), but that the context in which these chips appear within the entire scene is also of importance to an image analyst. The term "intelligent" is used to signify an external cuer which locates the chips of interest.
{"title":"Intelligent low rate compression of speckled SAR imagery","authors":"R. Ives, P. Eichel, N. Magotra","doi":"10.1109/NRC.1998.678007","DOIUrl":"https://doi.org/10.1109/NRC.1998.678007","url":null,"abstract":"This paper describes a compression technique under development at Sandia National Laboratories for the compression of complex synthetic aperture radar (SAR) imagery at very low overall bit rates. The methods involved combine several elements of existing and new lossy and lossless compression schemes in order to achieve an overall compression ratio of large SAR scenes of at least 50:1, while maintaining reasonable image quality. It is assumed that the end user will be primarily interested in specific regions of interest within the image (called \"chips\"), but that the context in which these chips appear within the entire scene is also of importance to an image analyst. The term \"intelligent\" is used to signify an external cuer which locates the chips of interest.","PeriodicalId":432418,"journal":{"name":"Proceedings of the 1998 IEEE Radar Conference, RADARCON'98. Challenges in Radar Systems and Solutions (Cat. No.98CH36197)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114411891","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 detector for the case of a radar target with known Doppler and unknown complex amplitude in colored noise of unknown covariance has been derived. The detector assumes that the noise is an autoregressive process and estimates the unknown parameters by maximum likelihood estimation for the use in the generalized likelihood ratio test. The asymptotic performance of this detector has been derived and it has been shown that for large data records this detector is CFAR. By computer simulation it has been shown that for a moderate size of data record, the performance of this detector approaches the asymptotic results.
{"title":"An auto-regressive GLR algorithm for adaptive radar detection","authors":"A. Sheikhi, M. Nayebi","doi":"10.1109/NRC.1998.678016","DOIUrl":"https://doi.org/10.1109/NRC.1998.678016","url":null,"abstract":"A detector for the case of a radar target with known Doppler and unknown complex amplitude in colored noise of unknown covariance has been derived. The detector assumes that the noise is an autoregressive process and estimates the unknown parameters by maximum likelihood estimation for the use in the generalized likelihood ratio test. The asymptotic performance of this detector has been derived and it has been shown that for large data records this detector is CFAR. By computer simulation it has been shown that for a moderate size of data record, the performance of this detector approaches the asymptotic results.","PeriodicalId":432418,"journal":{"name":"Proceedings of the 1998 IEEE Radar Conference, RADARCON'98. Challenges in Radar Systems and Solutions (Cat. No.98CH36197)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123014287","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 major problem that occurs in constant false alarm rate (CFAR) schemes is presented by regions of nonhomogeneous clutter background. The situation occurs when the total noise power received in a single reference window does not follow the assumption of independent and identically distributed clutter in all reference window cells. Bayesian statistics provide a mathematical procedure for changing or updating the degree of belief about the clutter parameter in light of more recent information. A Bayesian CFAR (Bay-CFAR) processor is developed and analyzed. The Bay-CFAR processor exploits a priori knowledge of a nonhomogeneous clutter environment to considerably improve the detection performance relative to a classical cell averaging CFAR (CA-CFAR) processor. The performance improvement is demonstrated with a small reference window size that allows the processor to respond quickly to a rapidly changing clutter environment.
{"title":"Description and analysis of a Bayesian CFAR radar signal processor in a nonhomogeneous clutter background","authors":"R.C. Colgin","doi":"10.1109/NRC.1998.677968","DOIUrl":"https://doi.org/10.1109/NRC.1998.677968","url":null,"abstract":"A major problem that occurs in constant false alarm rate (CFAR) schemes is presented by regions of nonhomogeneous clutter background. The situation occurs when the total noise power received in a single reference window does not follow the assumption of independent and identically distributed clutter in all reference window cells. Bayesian statistics provide a mathematical procedure for changing or updating the degree of belief about the clutter parameter in light of more recent information. A Bayesian CFAR (Bay-CFAR) processor is developed and analyzed. The Bay-CFAR processor exploits a priori knowledge of a nonhomogeneous clutter environment to considerably improve the detection performance relative to a classical cell averaging CFAR (CA-CFAR) processor. The performance improvement is demonstrated with a small reference window size that allows the processor to respond quickly to a rapidly changing clutter environment.","PeriodicalId":432418,"journal":{"name":"Proceedings of the 1998 IEEE Radar Conference, RADARCON'98. Challenges in Radar Systems and Solutions (Cat. No.98CH36197)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125453349","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 newly compiled International Radar Directory CD-ROM resulted from a twenty year collection effort by this author of open information on radars of the world. During World War II radars were made in only a few countries, but are now manufactured in many countries. Radar applications now included number some 50. Radar is frequently teamed with military IR/EO/laser/weapon systems; however, in many of these the radar is sometimes not given its own type designation. Thus it is appropriate to include IR/EO/laser/weapon systems in this Directory CD-ROM on current radar systems. This paper describes the 1998 Directory CD-ROM and presents an illustrative example of use of information contained in it: who makes what and where. Consideration is given to adding the large number of past radars to a future Directory CD-ROM.
{"title":"The International Radar Directory: who makes what and where","authors":"S. Johnston","doi":"10.1109/NRC.1998.677981","DOIUrl":"https://doi.org/10.1109/NRC.1998.677981","url":null,"abstract":"The newly compiled International Radar Directory CD-ROM resulted from a twenty year collection effort by this author of open information on radars of the world. During World War II radars were made in only a few countries, but are now manufactured in many countries. Radar applications now included number some 50. Radar is frequently teamed with military IR/EO/laser/weapon systems; however, in many of these the radar is sometimes not given its own type designation. Thus it is appropriate to include IR/EO/laser/weapon systems in this Directory CD-ROM on current radar systems. This paper describes the 1998 Directory CD-ROM and presents an illustrative example of use of information contained in it: who makes what and where. Consideration is given to adding the large number of past radars to a future Directory CD-ROM.","PeriodicalId":432418,"journal":{"name":"Proceedings of the 1998 IEEE Radar Conference, RADARCON'98. Challenges in Radar Systems and Solutions (Cat. No.98CH36197)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115542993","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}
J. Kirk, R. Lefevre, R. Durand, L. Bui, R. Zelenka, B. Sridhar
Under a Phase II SBIR from NASA, a data collection radar was developed to support the NASA program in Automated Napof the Earth (ANOE) guidance for helicopters. The developed radar is comprised of two parts, a sensor front end and a digital signal processor. The sensor front end is a wideband, linear FM, 94 GHz millimeter wave radar with dual circular polarization and dual axis monopulse. It provides 10 dB signal-to-noise on a 5 m/sup 2/ target at 1 km. Digital signal processing is employed to provide range compression and monopulse angle beam sharpening. To remain within funding limitations the radar generates a reduced size raster scan of 12.5/spl deg/ /spl times/250/spl times/320 m for collecting data. The range resolution is 3 m, the angle bin size is 0.34/spl deg/, and there is frequency agility over 600 MHz. Data was collected from a ground location to verify operation of the radar. The data is displayed in a C-scope format using NASA supplied "Grid World" software.
{"title":"Automated Nap of the Earth (ANOE) data collection radar","authors":"J. Kirk, R. Lefevre, R. Durand, L. Bui, R. Zelenka, B. Sridhar","doi":"10.1109/NRC.1998.677971","DOIUrl":"https://doi.org/10.1109/NRC.1998.677971","url":null,"abstract":"Under a Phase II SBIR from NASA, a data collection radar was developed to support the NASA program in Automated Napof the Earth (ANOE) guidance for helicopters. The developed radar is comprised of two parts, a sensor front end and a digital signal processor. The sensor front end is a wideband, linear FM, 94 GHz millimeter wave radar with dual circular polarization and dual axis monopulse. It provides 10 dB signal-to-noise on a 5 m/sup 2/ target at 1 km. Digital signal processing is employed to provide range compression and monopulse angle beam sharpening. To remain within funding limitations the radar generates a reduced size raster scan of 12.5/spl deg/ /spl times/250/spl times/320 m for collecting data. The range resolution is 3 m, the angle bin size is 0.34/spl deg/, and there is frequency agility over 600 MHz. Data was collected from a ground location to verify operation of the radar. The data is displayed in a C-scope format using NASA supplied \"Grid World\" software.","PeriodicalId":432418,"journal":{"name":"Proceedings of the 1998 IEEE Radar Conference, RADARCON'98. Challenges in Radar Systems and Solutions (Cat. No.98CH36197)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116546779","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：