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Tracking sound speed field under internal wave perturbation with the unscented Kalman filter

机译:使用无味卡尔曼滤波器跟踪内部波扰动下的声速场

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Model-based signal processing methods, such as matched-field processing, are concerned with exploiting the combination of the sound propagation physics in an ocean waveguide and the observation data. As such, they require accurate knowledge of the ocean acoustic environment. Tracking of environmental uncertainties is of great interest for model-based signal processing. This paper further develops the approach of acoustic data assimilation (ADA) for tracking the sound speed field under internal wave perturbations. Specifically, the sequential method of the UKF is used to implement the ADA for solving the nonlinear tracking problem. The simulation results demonstrate the validity of the developed approach.
机译:基于模型的信号处理方法(例如匹配场处理)与利用海洋波导中的声音传播物理学和观测数据的组合有关。因此,他们需要准确了解海洋声学环境。跟踪环境不确定性对于基于模型的信号处理非常重要。本文进一步发展了一种在内部波扰动下跟踪声速场的声学数据同化(ADA)方法。具体地,使用UKF的顺序方法来实现ADA,以解决非线性跟踪问题。仿真结果证明了该方法的有效性。

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