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Underwater mobile target tracking with particle filter using an autonomous vehicle

机译:使用自主车辆与粒子过滤器的水下移动目标跟踪

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This paper describes an underwater mobile target localization and tracking by using an autonomous surface vehicle for which the successive ranges between the target and the reference are the only information. In a dynamic system, such as range-only single-beacon underwater target tracking, a state-space model can be characterized, where the state vector may include position, and velocity of the mobile underwater target. Moreover, the range observations can come from a mobile autonomous vehicle, which is used as a moving landmark. Then, a nonlinear Bayesian filtering algorithm can be used to make extrapolations on the state vector from the observations, in order to obtain the target position at each instant of time. In this paper we consider the use of Particle Filter (PF) to perform such localization and tracking where its performance and characterization is studied under different scenarios.
机译:本文通过使用自主表面车辆来介绍水下移动目标本地化和跟踪,目标和参考之间的连续范围是唯一的信息。在动态系统中,例如仅限范围单信标水下目标跟踪,可以表征状态空间模型,其中状态向量可以包括移动水下目标的位置和速度。此外,范围观察可以来自移动自动车辆,其用作移动地标。然后,可以使用非线性贝叶斯滤波算法来使来自观察结果的状态向量上的外推,以便在每个时刻获得目标位置。在本文中,我们考虑使用粒子过滤器(PF)来执行这种定位和跟踪,其中在不同场景下研究了其性能和表征。

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