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An expectation-maximization based single-beacon underwater navigation method with unknown ESV

机译:ESV未知的基于期望最大化的单信标水下导航方法

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Navigation performance in a single-beacon underwater navigation system considerably depends on the accuracy of the slant-range measurement. Ranges are usually obtained based on a presumed or known effective sound velocity (ESV). Because it is difficult to accurately determine the ESV between the pinger and the receiver, traditional methods are usually affected by large-range measurement errors that lead to large positioning errors. In this study, we use the expectation maximization (EM) method, which is widely used for parameter identification, to estimate the unknown ESV by treating it as a model parameter. We propose an EM-based, single-beacon navigation method that incorporates the Kalman filter into the EM frame. Numerical examples using simulated and field data indicate that navigation accuracy can be significantly improved when the proposed EM-based method is implemented, and the estimated ESV is in good agreement with its true value. (C) 2019 The Authors. Published by Elsevier B.V.
机译:单信标水下导航系统中的导航性能在很大程度上取决于斜距测量的准确性。通常根据假定的或已知的有效声速(ESV)获得范围。由于很难准确确定pinger与接收器之间的ESV,因此传统方法通常会受到较大范围的测量误差的影响,从而导致较大的定位误差。在这项研究中,我们使用广泛用于参数识别的期望最大化(EM)方法,通过将其视为模型参数来估计未知ESV。我们提出了一种基于EM的单信标导航方法,该方法将Kalman滤波器合并到EM框架中。使用模拟和现场数据的数值示例表明,当实施所提出的基于EM的方法时,导航精度可以得到显着提高,并且估计的ESV与其真实值非常吻合。 (C)2019作者。由Elsevier B.V.发布

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