Pub Date : 2007-06-04DOI: 10.1109/CAMAP.2005.1574208
H.H. Sneesens, L. Vandendorpe
Mobile receivers can benefit from an increased spatial diversity through cooperation. Two relaying techniques are typically used: either amplify and forward (AF) or decode and forward (DF). This contribution presents a new technique, which combines the main advantages of both AF and DF. This technique amounts to a DF scheme where all operations are performed in a soft-input soft-output fashion. In particular, an encoding technique which uses soft values to incorporate reliability information is proposed. The resulting soft-DF relay can be seen as an analog signal-to-noise ratio enhancer. Simulations show that this soft-DF scheme outperforms both AF and DF
{"title":"Soft decode and forward improves cooperative communications","authors":"H.H. Sneesens, L. Vandendorpe","doi":"10.1109/CAMAP.2005.1574208","DOIUrl":"https://doi.org/10.1109/CAMAP.2005.1574208","url":null,"abstract":"Mobile receivers can benefit from an increased spatial diversity through cooperation. Two relaying techniques are typically used: either amplify and forward (AF) or decode and forward (DF). This contribution presents a new technique, which combines the main advantages of both AF and DF. This technique amounts to a DF scheme where all operations are performed in a soft-input soft-output fashion. In particular, an encoding technique which uses soft values to incorporate reliability information is proposed. The resulting soft-DF relay can be seen as an analog signal-to-noise ratio enhancer. Simulations show that this soft-DF scheme outperforms both AF and DF","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115097280","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 : 2005-12-13DOI: 10.1109/CAMAP.2005.1574197
A. Morell, A. Pascual-Iserte, A. Pérez-Neira, M. Lagunas
This paper proposes a new technique in the context of multi-user scheduling in orthogonal frequency division multiplexing (OFDM) and multi-input-multi-output (MIMO) systems by considering a design that is also robust to channel uncertainties. The whole technique is divided into two parts: i) a robust design for each particular MIMO link exploiting an imperfect channel state information (CSI) and ii) a multi-user design for the scheduling policy. The link between both stages is practical, intuitive, and simple. The robust MIMO design is based on a worst-case approach that maximizes via convex optimization procedures the worst possible signal to noise ratio (SNR) given a specified channel uncertainty region. The scheduling policy, also calculated with convex optimization techniques, minimizes the total number of utilized subcarriers. Therefore, the design is scalable in the sense of having the capability to incorporate new future potential users.
{"title":"Robust scheduling in MIMO-OFDM multi-user systems based on convex optimization","authors":"A. Morell, A. Pascual-Iserte, A. Pérez-Neira, M. Lagunas","doi":"10.1109/CAMAP.2005.1574197","DOIUrl":"https://doi.org/10.1109/CAMAP.2005.1574197","url":null,"abstract":"This paper proposes a new technique in the context of multi-user scheduling in orthogonal frequency division multiplexing (OFDM) and multi-input-multi-output (MIMO) systems by considering a design that is also robust to channel uncertainties. The whole technique is divided into two parts: i) a robust design for each particular MIMO link exploiting an imperfect channel state information (CSI) and ii) a multi-user design for the scheduling policy. The link between both stages is practical, intuitive, and simple. The robust MIMO design is based on a worst-case approach that maximizes via convex optimization procedures the worst possible signal to noise ratio (SNR) given a specified channel uncertainty region. The scheduling policy, also calculated with convex optimization techniques, minimizes the total number of utilized subcarriers. Therefore, the design is scalable in the sense of having the capability to incorporate new future potential users.","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129288949","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 : 2005-12-13DOI: 10.1109/CAMAP.2005.1574218
V. Bezruk
Some practical peculiarities of random signals recognition methods are considered for non-traditional cases when the signals with unknown probabilistic characteristics are presented for recognition along with the signals predetermined in a probabilistic sense. The distinctive peculiarities of the present work is that it considers the solution signals recognition problem on the basis of different probabilistic models - in the form of autoregression processes, mixtures of standard distributions, expansions in orthogonal functions of random signals. The data on decision of recognition problems are considered. In particular, that is decision the different problems of recognition signals for radio control, recognition of any types of targets by signals features using narrow-bend signals and recognition signals for medical diagnostic
{"title":"Recognition of the predetermined random signals involving the unknown signals","authors":"V. Bezruk","doi":"10.1109/CAMAP.2005.1574218","DOIUrl":"https://doi.org/10.1109/CAMAP.2005.1574218","url":null,"abstract":"Some practical peculiarities of random signals recognition methods are considered for non-traditional cases when the signals with unknown probabilistic characteristics are presented for recognition along with the signals predetermined in a probabilistic sense. The distinctive peculiarities of the present work is that it considers the solution signals recognition problem on the basis of different probabilistic models - in the form of autoregression processes, mixtures of standard distributions, expansions in orthogonal functions of random signals. The data on decision of recognition problems are considered. In particular, that is decision the different problems of recognition signals for radio control, recognition of any types of targets by signals features using narrow-bend signals and recognition signals for medical diagnostic","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114826985","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 : 2005-12-13DOI: 10.1109/CAMAP.2005.1574195
G. San Antonio, D. Fuhrmann
A MIMO radar system is a radar system with multiple transmitters, each driven with its own signal, coherently with all the other transmitters. In this paper we consider the problem of using this flexibility to transmit wideband signals and control the spatial distribution of transmitted power. We show how the power distribution is a function of the signal cross-spectral density matrix (CSDM), and formulate the problem of determining the CSDM that generates a desired spatial beampattern subject to power constraints on the transmitters. Convex optimization techniques are used to find the numerical solution of the resulting optimization problem.
{"title":"Beampattern synthesis for wideband MIMO radar systems","authors":"G. San Antonio, D. Fuhrmann","doi":"10.1109/CAMAP.2005.1574195","DOIUrl":"https://doi.org/10.1109/CAMAP.2005.1574195","url":null,"abstract":"A MIMO radar system is a radar system with multiple transmitters, each driven with its own signal, coherently with all the other transmitters. In this paper we consider the problem of using this flexibility to transmit wideband signals and control the spatial distribution of transmitted power. We show how the power distribution is a function of the signal cross-spectral density matrix (CSDM), and formulate the problem of determining the CSDM that generates a desired spatial beampattern subject to power constraints on the transmitters. Convex optimization techniques are used to find the numerical solution of the resulting optimization problem.","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130817097","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 : 2005-12-13DOI: 10.1109/CAMAP.2005.1574210
Y. Shkvarko, I. Villalón-Turrubiates
In this paper, the problem of estimating from a finite set of measurements of the radar remotely sensed complex data signals, the power spatial spectrum pattern (SSP) of the wavefield sources distributed in the environment is cast in the framework of Bayesian minimum risk (MR) paradigm unified with the experiment design (ED) regularization technique. The fused MR-ED regularization of the ill-posed nonlinear inverse problem of the SSP reconstruction is performed via incorporating into the MR estimation strategy the projection-regularization ED constraints. The simulation examples are incorporated to illustrate the efficiency of the proposed unified MR-ED technique
{"title":"Unified Bayesian-experiment design regularization technique for high-resolution reconstruction of the remote sensing imagery","authors":"Y. Shkvarko, I. Villalón-Turrubiates","doi":"10.1109/CAMAP.2005.1574210","DOIUrl":"https://doi.org/10.1109/CAMAP.2005.1574210","url":null,"abstract":"In this paper, the problem of estimating from a finite set of measurements of the radar remotely sensed complex data signals, the power spatial spectrum pattern (SSP) of the wavefield sources distributed in the environment is cast in the framework of Bayesian minimum risk (MR) paradigm unified with the experiment design (ED) regularization technique. The fused MR-ED regularization of the ill-posed nonlinear inverse problem of the SSP reconstruction is performed via incorporating into the MR estimation strategy the projection-regularization ED constraints. The simulation examples are incorporated to illustrate the efficiency of the proposed unified MR-ED technique","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131004017","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 : 2005-12-13DOI: 10.1109/CAMAP.2005.1574213
H. I. Piza, F. F. Ramos, F. Zúñiga
This paper proposes a sensor-based mechanism that allows virtual creatures to perceive the environment that surrounds them. We are keen on modeling the behavior of real-life creatures via VR-techniques. Every living creature is endowed by a number of senses, by means of which, the creature is aware of the world around. We picture the environment as a multi-agent system, where every agent has, primarily, a knowledge base, a sensors and effectors to allow interaction. The effectors may launch actions (graphical changes), noises, messages or aromas. The sensors model, particularly, the sight, hearing and smell senses of a living creature. Every sensor has specific perception capabilities and gathers partial or full information about the objects around. Through the sensors, a virtual creature is aware of the environment and capable to increase the knowledge base. The local state of a creature can be amplified by allowing cooperation between agents
{"title":"Virtual sensors for dynamic virtual environments","authors":"H. I. Piza, F. F. Ramos, F. Zúñiga","doi":"10.1109/CAMAP.2005.1574213","DOIUrl":"https://doi.org/10.1109/CAMAP.2005.1574213","url":null,"abstract":"This paper proposes a sensor-based mechanism that allows virtual creatures to perceive the environment that surrounds them. We are keen on modeling the behavior of real-life creatures via VR-techniques. Every living creature is endowed by a number of senses, by means of which, the creature is aware of the world around. We picture the environment as a multi-agent system, where every agent has, primarily, a knowledge base, a sensors and effectors to allow interaction. The effectors may launch actions (graphical changes), noises, messages or aromas. The sensors model, particularly, the sight, hearing and smell senses of a living creature. Every sensor has specific perception capabilities and gathers partial or full information about the objects around. Through the sensors, a virtual creature is aware of the environment and capable to increase the knowledge base. The local state of a creature can be amplified by allowing cooperation between agents","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132433396","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 : 2005-12-13DOI: 10.1109/CAMAP.2005.1574222
M. Bondarenko, D. I. Lekhovitsky
A unified approach for the implementation of DOA estimation algorithms for some number of point sources is proposed and analyzed, based on adaptive lattice filters. The important advantages of this approach with respect to eigensubspace techniques such as MUSIC, are demonstrated for practical applications
{"title":"Combined direction finders of point noise radiation sources in AA based on adaptive lattice filters","authors":"M. Bondarenko, D. I. Lekhovitsky","doi":"10.1109/CAMAP.2005.1574222","DOIUrl":"https://doi.org/10.1109/CAMAP.2005.1574222","url":null,"abstract":"A unified approach for the implementation of DOA estimation algorithms for some number of point sources is proposed and analyzed, based on adaptive lattice filters. The important advantages of this approach with respect to eigensubspace techniques such as MUSIC, are demonstrated for practical applications","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114979162","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 : 2005-12-13DOI: 10.1109/CAMAP.2005.1574223
M. Bondarenko, D.I. Lekhovitsky
The "statistical" rates of convergence of a number of Gaussian coherent signal adaptive detectors with the maximum likelihood estimation of a Gaussian interference correlation matrix are compared, and recommendations on their practical application are given
{"title":"Choice of learning sample size in adaptive detectors of signals against a background of Gaussian interference","authors":"M. Bondarenko, D.I. Lekhovitsky","doi":"10.1109/CAMAP.2005.1574223","DOIUrl":"https://doi.org/10.1109/CAMAP.2005.1574223","url":null,"abstract":"The \"statistical\" rates of convergence of a number of Gaussian coherent signal adaptive detectors with the maximum likelihood estimation of a Gaussian interference correlation matrix are compared, and recommendations on their practical application are given","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129714787","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 : 2005-12-13DOI: 10.1109/CAMAP.2005.1574175
A. Ashtari, D. Flores-Tapia, G. Thomas, S. Pistorius
Imaging of buried objects using subsurface microwave technology can result in images with numerous undesirable artifacts due in part to noise and multipath scattering. In order to alleviate the problem of multipath scattering, the authors propose the combined use of monostatic and bistatic systems. Focusing both images and compensating the bistatic system enables us to place the direct path scatterers at the same position as in the monostatic case. A multiplication of the final images will attenuate the scatterers that are formed by multiple reflections and will therefore reduce artifacts. Results are shown using simulations in which the signatures of several point scatterers overlap for the direct reflections and where the multipath signatures do not; thus allowing the multiplication to enhance the final image.
{"title":"A method for combining focused monostatic and bistatic GPR to reduce multipath effects","authors":"A. Ashtari, D. Flores-Tapia, G. Thomas, S. Pistorius","doi":"10.1109/CAMAP.2005.1574175","DOIUrl":"https://doi.org/10.1109/CAMAP.2005.1574175","url":null,"abstract":"Imaging of buried objects using subsurface microwave technology can result in images with numerous undesirable artifacts due in part to noise and multipath scattering. In order to alleviate the problem of multipath scattering, the authors propose the combined use of monostatic and bistatic systems. Focusing both images and compensating the bistatic system enables us to place the direct path scatterers at the same position as in the monostatic case. A multiplication of the final images will attenuate the scatterers that are formed by multiple reflections and will therefore reduce artifacts. Results are shown using simulations in which the signatures of several point scatterers overlap for the direct reflections and where the multipath signatures do not; thus allowing the multiplication to enhance the final image.","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130743381","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 : 2005-12-13DOI: 10.1109/CAMAP.2005.1574220
Huang Qi, X. Tao, Liu Hai Tao
This paper considers the problem of classifying simultaneous multiple ground vehicles using their acoustic signatures recorded by unattended passive acoustic sensor array. The proposed approach relies on the blind source separation (BSS) algorithm based on time-frequency signal representations. Instead of estimating mixing parameters as the original algorithm do, we get the missing feature mask from the BSS step. Then an acoustic signature recognizer based on the missing feature theory recognizes each acoustic source. Recognition results are presented for several simultaneous vehicle acoustic signals. Compared with familiar ways, using both the missing feature theory and BSS algorithm results in high performance improvement
{"title":"Multiple target recognition based on blind source separation and missing feature theory","authors":"Huang Qi, X. Tao, Liu Hai Tao","doi":"10.1109/CAMAP.2005.1574220","DOIUrl":"https://doi.org/10.1109/CAMAP.2005.1574220","url":null,"abstract":"This paper considers the problem of classifying simultaneous multiple ground vehicles using their acoustic signatures recorded by unattended passive acoustic sensor array. The proposed approach relies on the blind source separation (BSS) algorithm based on time-frequency signal representations. Instead of estimating mixing parameters as the original algorithm do, we get the missing feature mask from the BSS step. Then an acoustic signature recognizer based on the missing feature theory recognizes each acoustic source. Recognition results are presented for several simultaneous vehicle acoustic signals. Compared with familiar ways, using both the missing feature theory and BSS algorithm results in high performance improvement","PeriodicalId":281761,"journal":{"name":"1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005.","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131759630","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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