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Target Localization and Sensor Synchronization in the Presence of Data Association Uncertainty

机译:数据关联不确定性存在下的目标本地化和传感器同步

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In passive sensor networks, sensor registration and data association are two essential processes. Although these two processes affect each other, they are usually addressed separately. In this paper, we propose an algorithm to localize multiple targets and estimate sensor clock biases using time difference of arrival (TDOA) measurements in the presence of data association uncertainty. The problem is formulated as a multidimensional optimization problem, where the objective is to maximize the generalized likelihood of the associated measurements based on target position and sensor clock bias estimates. Computer simulations are carried out to evaluate the performance of the proposed algorithm.
机译:在被动传感器网络中,传感器注册和数据关联是两个基本过程。虽然这两个过程相互影响,但它们通常单独解决。在本文中,我们提出了一种算法来通过在存在数据关联不确定性的情况下使用时间差(TDOA)测量来定位多个目标和估计传感器时钟偏差。该问题被制定为多维优化问题,其中目标是基于目标位置和传感器时钟偏差估计最大化相关测量的广义似然。进行计算机仿真以评估所提出的算法的性能。

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