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Integrated Space-time Strategies for Imaging and Communication in Complex Environments

Integrated Space-time Strategies for Imaging and Communication in Complex Environments
复杂环境中成像和通信的综合时空策略
批准号:
0925034
负责人:
Yasuo Kuga
金额:
$23.86万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-15 至 2012-08-31

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中文摘要
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英文摘要
This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The objective of this research is the development of new generalized integrated imaging and communication technologies making use of recent studies on several techniques such as time-reversal imaging, correlation imaging, and array coherence tomographic imaging. These integrated techniques offer new areas of research with a potential for practical applications. The approach is the combined use of analytical, numerical and experimental studies for the specific topics of: (i) information fusion of multiple imaging sensors; (ii) coherent passive radars making use of angle-of-arrival estimation and ambiguity function; and (iii) research on communications through complex environments unifying propagation research and signal processing. Theories and computations are often based on assumptions and approximations and it is important to verify the results by experiments. This research includes experiments using the proposed methods to verify the theories and to point to new improvement of theories.The intellectual merit of this research is new theoretical foundations which unify propagation and scattering theories and signal processing research. These two areas are largely separately developed. This research, therefore, intends to focus on the unified treatment of space-time wave propagation and scattering, multiple imaging sensors, and signal processing.The broader impacts are the creation of new technologies which should help expand wireless communication and imaging in complex environments. The training and education of students is a priority. The dissemination of the results through classes helps students to understand new areas of integrated theories and measurement, statistical considerations, fusion of multiple imaging sensors, and signal processing.
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