| Project/Area Number |
14550344
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
情報通信工学
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| Research Institution | Kitami Institute of Technology |
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Principal Investigator |
SUZUKI Masakiyo Kitami Institute of Technology, Faculty of Engineering, Professor, 工学部, 教授 (60192621)
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| Project Period (FY) |
2002 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2004: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2003: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2002: ¥1,900,000 (Direct Cost: ¥1,900,000)
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| Keywords | Localization / Derection-of-Arrival Estimation / Signal Number Detection / Coherent Signal / Small Number of Samples / Efficient Algorithm / Migration of Salmon / Automatic Chasing System / 音源定位 / ディジタル信号処理 / サケ自動追跡 / ロボット船 / 超音波 / センサアレイ / サケの回遊行動 |
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| Research Abstract |
The detection of the number of superimposed signals and signal source localization or direction-of-arrival (DOA) finding are the most basic and important issues in the research fields of radar, sonar, seismology, radio astronomy, mobile communications, biomedical engineering, and so on. In this research, we have developed novel efficient algorithms with super-resolution or high accuracy for the problems of the detection and the DOA estimation in the noisy environment.
1.In the case that the environment of receiving signals varies, the received signal could not be dealt with as stationary. Only small number of samples can be used to extract information from the received signals. We have developed the novel criterion to detect the number of signals using a very small number of samples.
2.Coherent signals received in the multi-path environment yield the deterioration of the quality of signals. We have developed the efficient algorithm for detecting the number of coherent signals.
3.Also we have developed the efficient algorithm for DOA finding of coherent signals.
4.For the research of the mechanism of salmon' s migration, we are developing a system which chases a salmon automatically. The multi-path environment deteriorates the performance of localizing the salmon. We are trying to apply our developed techniques to the system automatically chasing a salmon.
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