Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578370
R. Touzi, K. Raney
The method currently used for the phase measurement of a point target signal relies on the phase of the peak reflector response as the signal phase estimate. The peak method phase is analyzed and shown to be sensitive to focus setting as is the estimate of pulse magnitude. A new method based on the integration of complex data is proposed for estimation of signal parameters for a point target in the presence of clutter. The complex integration method is shown to be practically insensitive both in phase and magnitude to misfocussing. These results are confirmed using CCRS auto-focussed and defocussed complex data. INTRO D U C TI0 N
{"title":"On the Use of Complex Sar Data for Calibration","authors":"R. Touzi, K. Raney","doi":"10.1109/IGARSS.1992.578370","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578370","url":null,"abstract":"The method currently used for the phase measurement of a point target signal relies on the phase of the peak reflector response as the signal phase estimate. The peak method phase is analyzed and shown to be sensitive to focus setting as is the estimate of pulse magnitude. A new method based on the integration of complex data is proposed for estimation of signal parameters for a point target in the presence of clutter. The complex integration method is shown to be practically insensitive both in phase and magnitude to misfocussing. These results are confirmed using CCRS auto-focussed and defocussed complex data. INTRO D U C TI0 N","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116579563","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 : 1992-05-26DOI: 10.1109/IGARSS.1992.578341
Jenq-Neng Hwang, D. T. Davis, L. Tsang
In most remote sensing applications, the forward probiem denotes the calculation of fields and waves from given parameters of the media. The inverse problem is to calculate the target or media parameters from measured fields and waves through relevant remote sensing electromagnetic theory. One of the most important steps of applying artificial neural networks (ANNs) to solve parameter inversion problems in remote sensing applications is to first establish a very reliable approximation of the true foryard mapping, y = Nx), based on an ANN approximation $, trained by data pairs of the media parameters x , and the measurements of the fields and waves y , generated through a rempte sensing electromagnetic model $' . While the trained A" $ can accurately approximate the electromagnetic model with negligible deviations, the degree of accurate ANN approximation of $' to the true mapping $ can only be verified by some available ground truth, which should be used to fine tune the trained ANN approximation $ . In this paper, we applied a minimum disturbance principle in fine tuning the approximated ANN by incorporating the small amount of available ground truth. More specifically, the ground truth is used to slightly modify the local vicinity of the mapping associated with this pair of training data without disturbing the whole mapping (i.e., without rocking the whole boat). This can be achieved by a locally tuned ANN formed by the radial basis functions, instead of the projection based ANN formed by the global logistic sigmoidal functions. FORWARD MODELS FOR INVERSE MODELS Remote sensing problems are of the general class of inverse problems, where we wish to infer the physical parameters which could cause a particular effect. Inverse problems admit of two lines of attack; creating a forward model of the process which then must be manipulated to yield an inverse [3], or creating an explicit inverse of the physical process [7]. An explicit inverse suffers from many-to-one problems when more than one cause could account for a particular effect. Forward models, on the other hand, can accurately model a causal relauonship. With a method of inverting the forward model, we can find a possible multiplicity of solutions from which we can select according to other information or additional constraints we wish to impose [ 11. The inversion of a forward model takes the form of a search in the input space of the model for an input which produces the desired output. With gradient information relating the input to some performance criteria, the search of the input space can proceed as a directed search, usually taken in the direction of this gradient. USE OF DATA DRIVEN MODELS WITH IMPLICIT FUNCTIONS There are three main types of forward models available: explicit functions, implicit functions, and data driven models. Explicit functions take the input and perform some direct functional mapping from input to output. To iteratively obtain an inverse. it is a simple matter
{"title":"A Locally Tuned Neural Network for Ground Truth Incorporation","authors":"Jenq-Neng Hwang, D. T. Davis, L. Tsang","doi":"10.1109/IGARSS.1992.578341","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578341","url":null,"abstract":"In most remote sensing applications, the forward probiem denotes the calculation of fields and waves from given parameters of the media. The inverse problem is to calculate the target or media parameters from measured fields and waves through relevant remote sensing electromagnetic theory. One of the most important steps of applying artificial neural networks (ANNs) to solve parameter inversion problems in remote sensing applications is to first establish a very reliable approximation of the true foryard mapping, y = Nx), based on an ANN approximation $, trained by data pairs of the media parameters x , and the measurements of the fields and waves y , generated through a rempte sensing electromagnetic model $' . While the trained A\" $ can accurately approximate the electromagnetic model with negligible deviations, the degree of accurate ANN approximation of $' to the true mapping $ can only be verified by some available ground truth, which should be used to fine tune the trained ANN approximation $ . In this paper, we applied a minimum disturbance principle in fine tuning the approximated ANN by incorporating the small amount of available ground truth. More specifically, the ground truth is used to slightly modify the local vicinity of the mapping associated with this pair of training data without disturbing the whole mapping (i.e., without rocking the whole boat). This can be achieved by a locally tuned ANN formed by the radial basis functions, instead of the projection based ANN formed by the global logistic sigmoidal functions. FORWARD MODELS FOR INVERSE MODELS Remote sensing problems are of the general class of inverse problems, where we wish to infer the physical parameters which could cause a particular effect. Inverse problems admit of two lines of attack; creating a forward model of the process which then must be manipulated to yield an inverse [3], or creating an explicit inverse of the physical process [7]. An explicit inverse suffers from many-to-one problems when more than one cause could account for a particular effect. Forward models, on the other hand, can accurately model a causal relauonship. With a method of inverting the forward model, we can find a possible multiplicity of solutions from which we can select according to other information or additional constraints we wish to impose [ 11. The inversion of a forward model takes the form of a search in the input space of the model for an input which produces the desired output. With gradient information relating the input to some performance criteria, the search of the input space can proceed as a directed search, usually taken in the direction of this gradient. USE OF DATA DRIVEN MODELS WITH IMPLICIT FUNCTIONS There are three main types of forward models available: explicit functions, implicit functions, and data driven models. Explicit functions take the input and perform some direct functional mapping from input to output. To iteratively obtain an inverse. it is a simple matter","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116689182","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 : 1992-05-26DOI: 10.1109/IGARSS.1992.578646
Q. Xiao, H. Raafat
Pattern recognition techniques currently used in remote sensing analysis are supervised and unsupervised classification methods. However, remotely sensed imagery can be distorted by many factors, for instance the surface slope, illumination and atmospheric effects, which will cause the classification errors. In order to improve classification accuracy, other types of information are needed such as the interrelationships between pixels or regions, previous classification results or existing map data, photometric or geometric properties on the area. This paper introduces an approach in which spatial information commonly stored in geographic information systems (GIS) is incorporated to assist the remote sensing image classification. The experimental results show that it is advantageous to use the spatial information in remote sensing analysis.
{"title":"Remote Sensing Image Classification By A Gis Guided Spatial Analysis","authors":"Q. Xiao, H. Raafat","doi":"10.1109/IGARSS.1992.578646","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578646","url":null,"abstract":"Pattern recognition techniques currently used in remote sensing analysis are supervised and unsupervised classification methods. However, remotely sensed imagery can be distorted by many factors, for instance the surface slope, illumination and atmospheric effects, which will cause the classification errors. In order to improve classification accuracy, other types of information are needed such as the interrelationships between pixels or regions, previous classification results or existing map data, photometric or geometric properties on the area. This paper introduces an approach in which spatial information commonly stored in geographic information systems (GIS) is incorporated to assist the remote sensing image classification. The experimental results show that it is advantageous to use the spatial information in remote sensing analysis.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124891632","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 : 1992-05-26DOI: 10.1109/IGARSS.1992.576738
L. Shemerl, M. Marom, D. Markman
Microwave remote sensing of the ocean surface using Synthetic Aperture Radar (SAR) is of great interest due to its high resolution and the potential of nearly instantaneous coverage of large areas. The present paper reports on measurements of ocean surface currents based on imaging of the nearshore regions of the Monterey Bay using an interferometric SAR (INSAR). The method is a modification of the conventional SAR which employs two spatially separated antennas. This modification provides direct mapping of the observed surface velocities. In particular, spatial distribution of the longshore current velocity is presented.
{"title":"Measurements Of Near Shore Ocean Currents Using Interiterferometric Aperture Radar","authors":"L. Shemerl, M. Marom, D. Markman","doi":"10.1109/IGARSS.1992.576738","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576738","url":null,"abstract":"Microwave remote sensing of the ocean surface using Synthetic Aperture Radar (SAR) is of great interest due to its high resolution and the potential of nearly instantaneous coverage of large areas. The present paper reports on measurements of ocean surface currents based on imaging of the nearshore regions of the Monterey Bay using an interferometric SAR (INSAR). The method is a modification of the conventional SAR which employs two spatially separated antennas. This modification provides direct mapping of the observed surface velocities. In particular, spatial distribution of the longshore current velocity is presented.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125671613","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 : 1992-05-26DOI: 10.1109/IGARSS.1992.576620
P. An, W. Moon, G. Bonham-Carter
An object-oriented and map-based prototype expert system is developed for integrating geophysical, geological, and remote sensing data for base metal exploration and tested using real exploration data from Farley Lake, Manitoba, Canada. Evidential belief function theory is utilized to manage the uncertainties in the system. The object-oriented knowledge representation structure and uncertainty propagation mechanisms used work well for this integrated exploration problem. In addition to other advantages of knowledge-based approach, the problem of dependent information can be dealt with in a knowledge-based system of this type by explicitly introducing important uncertainties and by organizing the relation network properly.
{"title":"On Knowledge-based Approach Of Integrating Remote Sensing, Geophysical And Geological Information","authors":"P. An, W. Moon, G. Bonham-Carter","doi":"10.1109/IGARSS.1992.576620","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576620","url":null,"abstract":"An object-oriented and map-based prototype expert system is developed for integrating geophysical, geological, and remote sensing data for base metal exploration and tested using real exploration data from Farley Lake, Manitoba, Canada. Evidential belief function theory is utilized to manage the uncertainties in the system. The object-oriented knowledge representation structure and uncertainty propagation mechanisms used work well for this integrated exploration problem. In addition to other advantages of knowledge-based approach, the problem of dependent information can be dealt with in a knowledge-based system of this type by explicitly introducing important uncertainties and by organizing the relation network properly.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122495342","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 : 1992-05-26DOI: 10.1109/IGARSS.1992.578415
K. Ranson, B. Rock, W. Salas, K. Smith, D.L. Williams
Data were collected for dominant conifer species. Dielectric properties of trunk wood were measured using a C-band dielectric probe. For certain specimens, electrical resistance was also measured using a shigometer. The water status of the trees studies was determined either by use of a Scholander pressure chamber on branch samples collected simultaneously with dielectric measurements or by fresh-weight/dry-weight assessment of wood core samples extracted and analyzed with the dielectric probe and shigometer. Diurnal delectric properties and xylem water column tension are inversely correlated such that real and imaginary dielectric values drop as tension increases. The dielectric properties were positively correlated with wood core moisture content while electrical resistance was poorly correlated with wood core moisture content in one species studied. Results support the view that dielectric properties are strongly correlated with moisture status in trunk wood, and possibly ion concentrations associated with decay processes in damaged specimens.
{"title":"Analysis of the Dielectric Properties of Trunk Wood in Dominant Conifer Species from New England and Siberia","authors":"K. Ranson, B. Rock, W. Salas, K. Smith, D.L. Williams","doi":"10.1109/IGARSS.1992.578415","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578415","url":null,"abstract":"Data were collected for dominant conifer species. Dielectric properties of trunk wood were measured using a C-band dielectric probe. For certain specimens, electrical resistance was also measured using a shigometer. The water status of the trees studies was determined either by use of a Scholander pressure chamber on branch samples collected simultaneously with dielectric measurements or by fresh-weight/dry-weight assessment of wood core samples extracted and analyzed with the dielectric probe and shigometer. Diurnal delectric properties and xylem water column tension are inversely correlated such that real and imaginary dielectric values drop as tension increases. The dielectric properties were positively correlated with wood core moisture content while electrical resistance was poorly correlated with wood core moisture content in one species studied. Results support the view that dielectric properties are strongly correlated with moisture status in trunk wood, and possibly ion concentrations associated with decay processes in damaged specimens.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122814918","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 : 1992-05-26DOI: 10.1109/IGARSS.1992.578376
J. Pulliainen, K. Heiska, J. Hyyppa, M. Hallikainen
This paper presents the results achieved from microwave radar backscattering measurements of defoliating spruces. Individual spruces were measured in an unechoic chamber and in outdoor conditions and the natural defoliation was simulated by gradually removing the needles of the trees. The measurements were carried out using 5/10 GHz and 35 GHz radar systems. The influence of defoliation to the volume backscattering and extinction coefficient of spruce canopy has been determined from the measured data. The results show that defoliation has a considerable effect on radar backscattering for 10 GHz linear polarizations. At 35 GHz the achieved data indicate a rather complicated and controversial backscattering behaviour with decreasing degree of defoliation. At 5 GHz the effect of defoliation on the backscattering coefficient is negligible. Helicopter-borne measurements of natural defoliation using the 5/10 GHz radar are presented for comparison. Additionally, measurements using a 90 GHz radiometer were conducted. But, by the time of preparing this paper the analysis of these results was not finalised.
{"title":"Laboratory and Tower-Based Microwave Measurements of Spruce Defoliation","authors":"J. Pulliainen, K. Heiska, J. Hyyppa, M. Hallikainen","doi":"10.1109/IGARSS.1992.578376","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578376","url":null,"abstract":"This paper presents the results achieved from microwave radar backscattering measurements of defoliating spruces. Individual spruces were measured in an unechoic chamber and in outdoor conditions and the natural defoliation was simulated by gradually removing the needles of the trees. The measurements were carried out using 5/10 GHz and 35 GHz radar systems. The influence of defoliation to the volume backscattering and extinction coefficient of spruce canopy has been determined from the measured data. The results show that defoliation has a considerable effect on radar backscattering for 10 GHz linear polarizations. At 35 GHz the achieved data indicate a rather complicated and controversial backscattering behaviour with decreasing degree of defoliation. At 5 GHz the effect of defoliation on the backscattering coefficient is negligible. Helicopter-borne measurements of natural defoliation using the 5/10 GHz radar are presented for comparison. Additionally, measurements using a 90 GHz radiometer were conducted. But, by the time of preparing this paper the analysis of these results was not finalised.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122821254","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 : 1992-05-26DOI: 10.1109/IGARSS.1992.576674
S. Falsaperla, L. Fortuna, S. Graziani, G. Nunnari
{"title":"Automatic Classification Of Seismic Events By Neural Networks","authors":"S. Falsaperla, L. Fortuna, S. Graziani, G. Nunnari","doi":"10.1109/IGARSS.1992.576674","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576674","url":null,"abstract":"","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131461960","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 : 1992-05-26DOI: 10.1109/IGARSS.1992.578879
L. Prévot, T. Schmugge
Because of their greater penetration depth in natural media, atmosphere and vegetation, microwave remote sensing techniques can overcome the limitations of the optical domain. As several imaging radars are already or to be launched during the coming decade, it is the most important to develop inversion algorithms allowing the use of radar data for estimating canopy characteristics such as biomass and leaf area index, as well as to correct estimations of surface soil moisture for the effect of vegetation.
{"title":"Combined Use of Theoretical and Semi-Empirical Models of Radar Backscattering to Estimate Characteristics of Vegetated Canopies","authors":"L. Prévot, T. Schmugge","doi":"10.1109/IGARSS.1992.578879","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578879","url":null,"abstract":"Because of their greater penetration depth in natural media, atmosphere and vegetation, microwave remote sensing techniques can overcome the limitations of the optical domain. As several imaging radars are already or to be launched during the coming decade, it is the most important to develop inversion algorithms allowing the use of radar data for estimating canopy characteristics such as biomass and leaf area index, as well as to correct estimations of surface soil moisture for the effect of vegetation.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131474151","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 : 1992-05-26DOI: 10.1109/IGARSS.1992.576786
M. Tovernd, P.A. ViUand, Y. Desnos, J. Gnignad
This paper describes, briefly, the implementation of a fast computer system capable of processing one lOOXlOO km ERS-1 S A R Fast Delivery product in 2 minutes. The development work is based on the Cesar computer system installed at the Troms0 Satellite Station in Norway. The paper describes the system in terms of architecture, programming environment and implementation of the SAR algorithm. The architecture introduces a programmable hardware implementation approach to algorithms through high order library functions, callable from a Unix environment. Parallelism with no communication overhead is achieved, providing high performance in vector computations.
本文简要介绍了一个快速计算机系统的实现，该系统能够在2分钟内处理一个lOOXlOO km - ers - 1rs快速交付产品。开发工作是基于安装在挪威Troms0卫星站的Cesar计算机系统。本文从系统的体系结构、编程环境和SAR算法的实现等方面对系统进行了描述。该体系结构引入了一种可编程的硬件实现方法，通过高阶库函数实现算法，可从Unix环境中调用。实现了无通信开销的并行性，为矢量计算提供了高性能。
{"title":"The Cesar Computer Architecture The Fastest Ers-1 Sar Processor In Europe","authors":"M. Tovernd, P.A. ViUand, Y. Desnos, J. Gnignad","doi":"10.1109/IGARSS.1992.576786","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576786","url":null,"abstract":"This paper describes, briefly, the implementation of a fast computer system capable of processing one lOOXlOO km ERS-1 S A R Fast Delivery product in 2 minutes. The development work is based on the Cesar computer system installed at the Troms0 Satellite Station in Norway. The paper describes the system in terms of architecture, programming environment and implementation of the SAR algorithm. The architecture introduces a programmable hardware implementation approach to algorithms through high order library functions, callable from a Unix environment. Parallelism with no communication overhead is achieved, providing high performance in vector computations.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131100798","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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