@InProceedings{6952712,
  author = {N. Sharaga and J. Tabrikian},
  booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},
  title = {Optimal adaptive transmit beamforming for cognitive MIMO sonar in a shallow water waveguide},
  year = {2014},
  pages = {1960-1964},
  abstract = {This paper addresses the problem of adaptive beamforming for target localization by active cognitive multiple-input multiple-output (MIMO) sonar in a shallow water waveguide. Recently, a sequential waveform design approach for estimation of parameters of a linear system was proposed. In this approach, at each step, the transmit beampattern is determined based on previous observations. The criterion used for waveform design is the Bayesian Cramér-Rao bound (BCRB) for estimation of the unknown system parameters. In this paper, this method is used for target localization in a shallow water waveguide, and it is extended to account for environmental uncertainties which are typical to underwater acoustic environments. The simulations show the sensitivity of the localization performance of the method at different environmental prior uncertainties.},
  keywords = {array signal processing;cognitive radio;MIMO communication;parameter estimation;sonar;optimal adaptive transmit beamforming;cognitive MIMO sonar;shallow water waveguide;adaptive beamforming;target localization;cognitive multiple-input multiple-output sonar;sequential waveform design;parameters estimation;linear system;Bayesian Cramér-Rao bound;underwater acoustic environments;Uncertainty;Array signal processing;Vectors;MIMO;Transmission line matrix methods;Adaptation models;Optimization;MIMO sonar;cognitive sonar;sequential waveform design;adaptive beamforming;underwater acoustics},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569927075.pdf},
}

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In this approach, at each step, the transmit beampattern is determined based on previous observations. The criterion used for waveform design is the Bayesian Cramér-Rao bound (BCRB) for estimation of the unknown system parameters. In this paper, this method is used for target localization in a shallow water waveguide, and it is extended to account for environmental uncertainties which are typical to underwater acoustic environments. The simulations show the sensitivity of the localization performance of the method at different environmental prior uncertainties.","keywords":"array signal processing;cognitive radio;MIMO communication;parameter estimation;sonar;optimal adaptive transmit beamforming;cognitive MIMO sonar;shallow water waveguide;adaptive beamforming;target localization;cognitive multiple-input multiple-output sonar;sequential waveform design;parameters estimation;linear system;Bayesian Cramér-Rao bound;underwater acoustic environments;Uncertainty;Array signal processing;Vectors;MIMO;Transmission line matrix methods;Adaptation models;Optimization;MIMO sonar;cognitive sonar;sequential waveform design;adaptive beamforming;underwater acoustics","issn":"2076-1465","month":"Sep.","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569927075.pdf","bibtex":"@InProceedings{6952712,\n author = {N. Sharaga and J. Tabrikian},\n booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},\n title = {Optimal adaptive transmit beamforming for cognitive MIMO sonar in a shallow water waveguide},\n year = {2014},\n pages = {1960-1964},\n abstract = {This paper addresses the problem of adaptive beamforming for target localization by active cognitive multiple-input multiple-output (MIMO) sonar in a shallow water waveguide. Recently, a sequential waveform design approach for estimation of parameters of a linear system was proposed. In this approach, at each step, the transmit beampattern is determined based on previous observations. The criterion used for waveform design is the Bayesian Cramér-Rao bound (BCRB) for estimation of the unknown system parameters. In this paper, this method is used for target localization in a shallow water waveguide, and it is extended to account for environmental uncertainties which are typical to underwater acoustic environments. The simulations show the sensitivity of the localization performance of the method at different environmental prior uncertainties.},\n keywords = {array signal processing;cognitive radio;MIMO communication;parameter estimation;sonar;optimal adaptive transmit beamforming;cognitive MIMO sonar;shallow water waveguide;adaptive beamforming;target localization;cognitive multiple-input multiple-output sonar;sequential waveform design;parameters estimation;linear system;Bayesian Cramér-Rao bound;underwater acoustic environments;Uncertainty;Array signal processing;Vectors;MIMO;Transmission line matrix methods;Adaptation models;Optimization;MIMO sonar;cognitive sonar;sequential waveform design;adaptive beamforming;underwater acoustics},\n issn = {2076-1465},\n month = {Sep.},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569927075.pdf},\n}\n\n","author_short":["Sharaga, N.","Tabrikian, J."],"key":"6952712","id":"6952712","bibbaseid":"sharaga-tabrikian-optimaladaptivetransmitbeamformingforcognitivemimosonarinashallowwaterwaveguide-2014","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569927075.pdf"},"keyword":["array signal processing;cognitive radio;MIMO communication;parameter estimation;sonar;optimal adaptive transmit beamforming;cognitive MIMO sonar;shallow water waveguide;adaptive beamforming;target localization;cognitive multiple-input multiple-output sonar;sequential waveform design;parameters estimation;linear system;Bayesian Cramér-Rao bound;underwater acoustic environments;Uncertainty;Array signal processing;Vectors;MIMO;Transmission line matrix methods;Adaptation models;Optimization;MIMO sonar;cognitive sonar;sequential waveform design;adaptive beamforming;underwater acoustics"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2014url.bib","creationDate":"2021-02-13T17:43:41.745Z","downloads":0,"keywords":["array signal processing;cognitive radio;mimo communication;parameter estimation;sonar;optimal adaptive transmit beamforming;cognitive mimo sonar;shallow water waveguide;adaptive beamforming;target localization;cognitive multiple-input multiple-output sonar;sequential waveform design;parameters estimation;linear system;bayesian cramér-rao bound;underwater acoustic environments;uncertainty;array signal processing;vectors;mimo;transmission line matrix methods;adaptation models;optimization;mimo sonar;cognitive sonar;sequential waveform design;adaptive beamforming;underwater acoustics"],"search_terms":["optimal","adaptive","transmit","beamforming","cognitive","mimo","sonar","shallow","water","waveguide","sharaga","tabrikian"],"title":"Optimal adaptive transmit beamforming for cognitive MIMO sonar in a shallow water waveguide","year":2014,"dataSources":["A2ezyFL6GG6na7bbs","oZFG3eQZPXnykPgnE"]}