Pub Date : 2004-04-26DOI: 10.1109/NRC.2004.1316496
B.E. Smith, T. Hale
The paper analyzes the effects of common data windows on STAP algorithms and the non-adaptive signal match processor. The windows are applied both to temporal and spatial dimensions. With the exception of factored approaches, it is shown that STAP algorithm performance decreases when windows are applied. Finally, a Monte Carlo analysis of probability of detection is performed on the best windowed/nonwindowed combination from each technique evaluated. Because the covariance must be estimated, the results demonstrate that the windowed non-adaptive signal match processor can outperform partially adaptive STAP methods at normalized Doppler between 0.25 and 0.75, while partially adaptive STAP algorithms perform significantly better than the windowed signal match processor closer to the clutter normalized Doppler.
{"title":"An analysis of the effects of windowing on selected STAP algorithms","authors":"B.E. Smith, T. Hale","doi":"10.1109/NRC.2004.1316496","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316496","url":null,"abstract":"The paper analyzes the effects of common data windows on STAP algorithms and the non-adaptive signal match processor. The windows are applied both to temporal and spatial dimensions. With the exception of factored approaches, it is shown that STAP algorithm performance decreases when windows are applied. Finally, a Monte Carlo analysis of probability of detection is performed on the best windowed/nonwindowed combination from each technique evaluated. Because the covariance must be estimated, the results demonstrate that the windowed non-adaptive signal match processor can outperform partially adaptive STAP methods at normalized Doppler between 0.25 and 0.75, while partially adaptive STAP algorithms perform significantly better than the windowed signal match processor closer to the clutter normalized Doppler.","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":"121664099","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.2004.1316434
S. Blunt, Karl Gerlach
Pulse compression is essentially an estimation procedure in which the complex amplitude for a given range cell is to be estimated while mitigating the interference from neighboring range cells that results from the convolution of the transmitted waveform with the range swath of interest. Traditionally, matched filtering is employed to estimate the range returns whereby the neighboring range cells are suppressed by a fixed amount that is dictated by the range sidelobes of the matched filter. However, matched filtering is a misnomer in that the receive filter is matched only to the transmitted waveform and not to the actual received signal. The paper extends the previously proposed reiterative minimum mean-square error (RMMSE) algorithm for adaptive pulse compression whereby the true matched filter for each individual range cell is estimated based upon the actual received signal resulting in range sidelobes that are adaptively suppressed to the level of the noise floor. The convergence of the RMMSE algorithm is addressed along with the Doppler tolerance.
{"title":"Adaptive pulse compression","authors":"S. Blunt, Karl Gerlach","doi":"10.1109/NRC.2004.1316434","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316434","url":null,"abstract":"Pulse compression is essentially an estimation procedure in which the complex amplitude for a given range cell is to be estimated while mitigating the interference from neighboring range cells that results from the convolution of the transmitted waveform with the range swath of interest. Traditionally, matched filtering is employed to estimate the range returns whereby the neighboring range cells are suppressed by a fixed amount that is dictated by the range sidelobes of the matched filter. However, matched filtering is a misnomer in that the receive filter is matched only to the transmitted waveform and not to the actual received signal. The paper extends the previously proposed reiterative minimum mean-square error (RMMSE) algorithm for adaptive pulse compression whereby the true matched filter for each individual range cell is estimated based upon the actual received signal resulting in range sidelobes that are adaptively suppressed to the level of the noise floor. The convergence of the RMMSE algorithm is addressed along with the Doppler tolerance.","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":"123328742","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.2004.1316455
N. Goodman, P. Gurram
In this paper, we investigate a spectral-domain approach to estimating the interference covariance matrix used in space-time adaptive processing. Traditionally, an estimate of the interference covariance matrix is obtained by averaging the space-time covariance matrices of multiple range bins. Unfortunately, the spectral content of these data snapshots usually varies, which corrupts the covariance estimate for the desired range. We propose to use knowledge sources to identify angle-Doppler spectral regions having the same underlying scattering statistics. Then, we use real-time data to form a synthetic aperture radar image, which is inherently an estimate of non-moving ground clutter. We then average the SAR pixels within each homogeneous region. The resulting clutter power map is used, along with knowledge of the radar system and scenario geometry, to compute the interference covariance matrix. Using simulated data, we demonstrate the potential performance of such a technique, demonstrate its dependence on accurate space-time steering vectors, and provide an example of using data to compensate for imperfect knowledge.
{"title":"STAP training through knowledge-aided predictive modeling [radar signal processing]","authors":"N. Goodman, P. Gurram","doi":"10.1109/NRC.2004.1316455","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316455","url":null,"abstract":"In this paper, we investigate a spectral-domain approach to estimating the interference covariance matrix used in space-time adaptive processing. Traditionally, an estimate of the interference covariance matrix is obtained by averaging the space-time covariance matrices of multiple range bins. Unfortunately, the spectral content of these data snapshots usually varies, which corrupts the covariance estimate for the desired range. We propose to use knowledge sources to identify angle-Doppler spectral regions having the same underlying scattering statistics. Then, we use real-time data to form a synthetic aperture radar image, which is inherently an estimate of non-moving ground clutter. We then average the SAR pixels within each homogeneous region. The resulting clutter power map is used, along with knowledge of the radar system and scenario geometry, to compute the interference covariance matrix. Using simulated data, we demonstrate the potential performance of such a technique, demonstrate its dependence on accurate space-time steering vectors, and provide an example of using data to compensate for imperfect knowledge.","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":"130969601","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.2004.1316398
E. Fishler, A. Haimovich, Rick S. Blum, Len Cimini, D. Chizhik, R. Valenzuela
It has recently been shown that multiple-input multiple-output (MIMO) antenna systems have the potential to improve dramatically the performance of communication systems over single antenna systems. Unlike beamforming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO concept exploits the independence between signals at the array elements. In conventional radar, target scintillations are regarded as a nuisance parameter that degrades radar performance. The novelty of MIMO radar is that it takes the opposite view; namely, it capitalizes on target scintillations to improve the radar's performance. We introduce the MIMO concept for radar. The MIMO radar system under consideration consists of a transmit array with widely-spaced elements such that each views a different aspect of the target. The array at the receiver is a conventional array used for direction finding (DF). The system performance analysis is carried out in terms of the Cramer-Rao bound of the mean-square error in estimating the target direction. It is shown that MIMO radar leads to significant performance improvement in DF accuracy.
{"title":"MIMO radar: an idea whose time has come","authors":"E. Fishler, A. Haimovich, Rick S. Blum, Len Cimini, D. Chizhik, R. Valenzuela","doi":"10.1109/NRC.2004.1316398","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316398","url":null,"abstract":"It has recently been shown that multiple-input multiple-output (MIMO) antenna systems have the potential to improve dramatically the performance of communication systems over single antenna systems. Unlike beamforming, which presumes a high correlation between signals either transmitted or received by an array, the MIMO concept exploits the independence between signals at the array elements. In conventional radar, target scintillations are regarded as a nuisance parameter that degrades radar performance. The novelty of MIMO radar is that it takes the opposite view; namely, it capitalizes on target scintillations to improve the radar's performance. We introduce the MIMO concept for radar. The MIMO radar system under consideration consists of a transmit array with widely-spaced elements such that each views a different aspect of the target. The array at the receiver is a conventional array used for direction finding (DF). The system performance analysis is carried out in terms of the Cramer-Rao bound of the mean-square error in estimating the target direction. It is shown that MIMO radar leads to significant performance improvement in DF accuracy.","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":"130879042","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.2004.1316482
L. Zhou, M. Patel, R. Spring, G. Strzalka, A. Daryoush
Digital receivers are pursued as part of future civilian and military applications. Design and implementation of a broadband receiver is presented that operates for radar applications at S-band. Performance of the realized hardware is evaluated in terms of system parameters.
{"title":"S-band integrated digital broadband receiver","authors":"L. Zhou, M. Patel, R. Spring, G. Strzalka, A. Daryoush","doi":"10.1109/NRC.2004.1316482","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316482","url":null,"abstract":"Digital receivers are pursued as part of future civilian and military applications. Design and implementation of a broadband receiver is presented that operates for radar applications at S-band. Performance of the realized hardware is evaluated in terms of system parameters.","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":"116092830","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.2004.1316466
Kun Lu, Xingzhao Liu
This paper describes a processing algorithm based on polynomial phase modeling scheme that increases visibility of maneuvering targets in HF over-the-horizon radar (OTHR). For the presence of the echo backscattered by the target that has significantly varying radial velocity within a coherent integration time (CIT), it is difficult for traditional coherent processing to centralize energy and peak in Doppler spectrum. Due to the polynomial property of the phase of maneuvering target radar echo, a polynomial phase signal (PPS) is introduced to model the complex Doppler variation of maneuvering targets. As an effective method to estimate the parameters of PPS, a high-order ambiguity function (HAF) based algorithm is applied. And a compensation process follows to eliminate the coherent processing loss (CIL) caused by irregular motion of targets. The experimental results are given to illustrate the validity and efficiency of the proposed method.
{"title":"Enhanced maneuvering targets detection via polynomial phase modeling in over-the-horizon radars","authors":"Kun Lu, Xingzhao Liu","doi":"10.1109/NRC.2004.1316466","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316466","url":null,"abstract":"This paper describes a processing algorithm based on polynomial phase modeling scheme that increases visibility of maneuvering targets in HF over-the-horizon radar (OTHR). For the presence of the echo backscattered by the target that has significantly varying radial velocity within a coherent integration time (CIT), it is difficult for traditional coherent processing to centralize energy and peak in Doppler spectrum. Due to the polynomial property of the phase of maneuvering target radar echo, a polynomial phase signal (PPS) is introduced to model the complex Doppler variation of maneuvering targets. As an effective method to estimate the parameters of PPS, a high-order ambiguity function (HAF) based algorithm is applied. And a compensation process follows to eliminate the coherent processing loss (CIL) caused by irregular motion of targets. The experimental results are given to illustrate the validity and efficiency 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":"122914991","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.2004.1316405
Frank, Reifler, Lockheed Martin
A filtering application of processing multisensor measurements with delays is considered. Because of delays, measurements fed by geographically dispersed sensors to a processing site may arrive out of time sequence. Unlike smoothing or filtering, optimal processing of an out-of-sequence measurement is not a standard problem in filtering theory for which a definitive approach has yet to be developed. An optimal reduced state estimator, derived in previous work, is applied to this problem. A simulation example of multisensor fusion is presented, in which one sensor feeds highly accurate, but delayed, measurements to be fused with a second sensor's less accurate measurements having no delay. We demonstrate a uniform improvement in performance for this algorithm over two traditional approaches.
{"title":"Application of reduced state estimation to multisensor fusion with out-of-sequence measurements","authors":"Frank, Reifler, Lockheed Martin","doi":"10.1109/NRC.2004.1316405","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316405","url":null,"abstract":"A filtering application of processing multisensor measurements with delays is considered. Because of delays, measurements fed by geographically dispersed sensors to a processing site may arrive out of time sequence. Unlike smoothing or filtering, optimal processing of an out-of-sequence measurement is not a standard problem in filtering theory for which a definitive approach has yet to be developed. An optimal reduced state estimator, derived in previous work, is applied to this problem. A simulation example of multisensor fusion is presented, in which one sensor feeds highly accurate, but delayed, measurements to be fused with a second sensor's less accurate measurements having no delay. We demonstrate a uniform improvement in performance for this algorithm over two traditional approaches.","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":"116467072","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.2004.1316416
S. Shank, W. Paterson, J. Johansson, L.M. Trevito
The paper describes the process employed to implement an advanced embedded signal processing subsystem for a legacy search digital signal processor (DSP), with emphasis on cost and open architecture (OA). This effort produced a low-cost, reconfigurable search DSP in a 15 month design cycle. A team of international partners was assembled, including Lockheed Martin Maritime Systems and Sensors (LM) (Moorestown, NJ), Indra Sistemas (Indra) (Madrid, Spain) and CSP Inc. (CSPI) (Billerica, MA). LM acted as the system design agent and was responsible for definition of the commercial off the shelf (COTS) architecture, technical requirements and fire control system (FCS) integration. Indra's responsibility was for software development that included the design, implementation and test of radar signal processing functions on general purpose processors. CSPI's responsibilities included providing development hardware, software, and training, as well as the development of a real-time interface to the legacy radar's processing cabinet.
{"title":"An open architecture for an embedded signal processing subsystem","authors":"S. Shank, W. Paterson, J. Johansson, L.M. Trevito","doi":"10.1109/NRC.2004.1316416","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316416","url":null,"abstract":"The paper describes the process employed to implement an advanced embedded signal processing subsystem for a legacy search digital signal processor (DSP), with emphasis on cost and open architecture (OA). This effort produced a low-cost, reconfigurable search DSP in a 15 month design cycle. A team of international partners was assembled, including Lockheed Martin Maritime Systems and Sensors (LM) (Moorestown, NJ), Indra Sistemas (Indra) (Madrid, Spain) and CSP Inc. (CSPI) (Billerica, MA). LM acted as the system design agent and was responsible for definition of the commercial off the shelf (COTS) architecture, technical requirements and fire control system (FCS) integration. Indra's responsibility was for software development that included the design, implementation and test of radar signal processing functions on general purpose processors. CSPI's responsibilities included providing development hardware, software, and training, as well as the development of a real-time interface to the legacy radar's processing cabinet.","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":"122356657","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.2004.1316469
M. Greco, F. Gini, A. Farina
This work presents a single-scan-processing approach to the problem of detecting and pre-classifying a radar target that may belong to different target classes. The proposed method is based on a hybrid of the maximum a posteriori (MAP) and Neyman-Pearson (NP) criteria and guarantees the desired constant false alarm rate (CFAR) behavior. The targets are modeled as subspace random signals having zero mean and given covariance matrix. Different target classes are discriminated based on their different signal subspaces, which are specified by their covariance matrices. Performance is investigated by means of numerical analysis and Monte Carlo simulation in terms of probabilities of false alarm, detection and classification. The extra signal-to-noise power ratio necessary to preclassify a target once a detection has occurred is also derived.
{"title":"A multiple hypotheses testing approach to radar detection and pre-classification","authors":"M. Greco, F. Gini, A. Farina","doi":"10.1109/NRC.2004.1316469","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316469","url":null,"abstract":"This work presents a single-scan-processing approach to the problem of detecting and pre-classifying a radar target that may belong to different target classes. The proposed method is based on a hybrid of the maximum a posteriori (MAP) and Neyman-Pearson (NP) criteria and guarantees the desired constant false alarm rate (CFAR) behavior. The targets are modeled as subspace random signals having zero mean and given covariance matrix. Different target classes are discriminated based on their different signal subspaces, which are specified by their covariance matrices. Performance is investigated by means of numerical analysis and Monte Carlo simulation in terms of probabilities of false alarm, detection and classification. The extra signal-to-noise power ratio necessary to preclassify a target once a detection has occurred is also derived.","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":"131102071","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.2004.1316409
P. Weber, A. Premji, T. Nohara, C. Krasnor
Low-cost radar systems have been developed for homeland security missions. These detect and track small maneuvering craft in the water. The systems consist of a conventional marine radar, a capture card that digitizes the radar signals, and a computer that processes them. We have an experimental system that can monitor western Lake Ontario. It runs in real time, with operator controls, and can store captured radar video. The achieved detection and tracking is demonstrated with recorded datasets. The combination of lower thresholds plus a sophisticated multi-target tracker gives excellent performance.
{"title":"Low-cost radar surveillance of inland waterways for homeland security applications","authors":"P. Weber, A. Premji, T. Nohara, C. Krasnor","doi":"10.1109/NRC.2004.1316409","DOIUrl":"https://doi.org/10.1109/NRC.2004.1316409","url":null,"abstract":"Low-cost radar systems have been developed for homeland security missions. These detect and track small maneuvering craft in the water. The systems consist of a conventional marine radar, a capture card that digitizes the radar signals, and a computer that processes them. We have an experimental system that can monitor western Lake Ontario. It runs in real time, with operator controls, and can store captured radar video. The achieved detection and tracking is demonstrated with recorded datasets. The combination of lower thresholds plus a sophisticated multi-target tracker gives excellent performance.","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":"132216583","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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