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| Statistical analysis method for time-varying underwater acoustic channel based on AR model |
| DAI Wenshu1, BAO Kaikai2, CHEN Xinhua3, SUN Xingli1 |
1. College of Information and Communication Engineering, North Unversity of China, Taiyuan 030051, China;
2. North Automatic Control Technology Institute, Taiyuan 030051, China;
3. The Institute of Acoustics of the Chinese Academy of Sciences, Beijing 100190, China |
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Abstract Bellhop beam tracking method can be used to get correct underwater acoustic channels under given geometry and sound source frequency with the ray theory, but it does not consider random channel changes. Here, the large-scale effect caused by position uncertainty and surface wave change was modeled as a first-order AR model. The relation among channel power gain, communication bandwidth and communication distance was theoretically modeled and analyzed, and this relation was verified with numerical simulation. The least square fitting was adopted to do local average of channel power gain, and then estimate the probability density function of a time-varying underwater acoustic channel. It was shown that time-varying surface waves can cause path length change; through calculating the auto-correlation function of channel power gain, the model parameters can be estimated to provide a possibility for channel prediction.
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Received: 16 May 2018
Published: 28 June 2019
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