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Parameter state estimation for bistatic sonar systems

机译:双基地声纳系统的参数状态估计

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The use of autonomous underwater vehicles (AUVs) cooperating in a network for anti-submarine warfare surveillance operations is of topical interest. Each AUV has to localise and track targets (submarines) robustly and precisely. This can be realised by a bistatic sonar configuration. The precise knowledge of the bistatic system parameters is mandatory for target tracking. These are in particular the positions of the acoustic sources, transmission times, and the position and heading of the AUV sonar sensor. However, these parameters often are not precisely known, e.g. for non-cooperative acoustic sources or due to navigation uncertainties of the AUV. Therefore, the authors consider the inverse problem, i.e. they estimate the bistatic system parameters by exploiting sonar echoes from known stationary `targets' like wrecks or small islands. Their implementation of the estimation method is based on the multihypothesis tracking technique. Results are discussed for two applications: The first one is estimation of the parameters of a non-cooperative source. The second application focuses on the estimation of the receiver parameters; in particular they show that their approach can be used to increase robustness of AUV navigation. Their algorithms are tested with simulated and real data recorded by the Centre for Maritime Research and Experimentation.
机译:在网络中合作使用自动驾驶水下航行器(AUV)进行反潜战监视操作引起了广泛的关注。每个AUV必须稳健而精确地定位和跟踪目标(潜艇)。这可以通过双基地声纳配置来实现。对双站系统参数的精确了解对于目标跟踪是必不可少的。这些尤其是声源的位置,传输时间以及AUV声纳传感器的位置和航向。然而,这些参数通常是不精确知道的,例如。用于非合作声源或AUV的导航不确定性。因此,作者考虑了反问题,即他们通过利用来自已知静止“目标”(如沉船或小岛)的声纳回波来估计双基地系统参数。他们对估计方法的实现是基于多假设跟踪技术的。讨论了两种应用的结果:第一种是对非合作来源参数的估计。第二个应用程序着重于接收机参数的估计。特别是,它们表明,他们的方法可用于提高AUV导航的鲁棒性。海事研究与实验中心记录的模拟和真实数据对他们的算法进行了测试。

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