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基于自相关估计和回波强度联合加权的多波束分层数据处理方法
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Abstract:
多波束水流测量因其宽覆盖、高精度、高效率等优点，正成为声学多普勒流速测量的一个热点。由于多波束流体回波数据相比常见的固定波束ADCP更加复杂，散射体速度不一致和分布非均匀等不稳定因素将会使得部分多波束分层数据质量较低，导致无法稳健获取流场时空分布特征。本文提出了一种基于自相关估计和回波强度联合加权的多波束分层数据处理方法，以改善数据的质量，减小测量的不确定性。仿真分析验证了方法的正确性与有效性。
Due to its wide coverage, high accuracy, high efficiency and other advantages, multi-beam flow measurement is becoming a hot spot in acoustic Doppler velocity measurement. Because the multi-beam fluid echo data is more complex than the common fixed-beam ADCP, the unstable factors such as the inconsistent velocity and the non-uniformity distribution of the scatters will make the quality of some radial velocity data and echo intensity data low, resulting in the inability to obtain the space-time distribution characteristics of the flow field robustly. In this paper, a multi-beam layered data processing method based on joint weighting with autocorrelation estimation and echo intensity is proposed to improve the quality of data and reduce the uncertainty of measurement. Simulation results demonstrated the correctness and effectiveness of the proposed method.
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