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Performance Improvement of AOA Positioning using A Two-Step Plan Based on Factor Graphs and the Gauss-Newton Method

机译：基于因子图和高斯 - 牛顿法，使用两步规划的AOA定位性能改进

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In this paper a two step method based on Gauss-Newton and factor graphs algorithm is proposed for localization to enhance accuracy of localization. The Gauss-Newton algorithm is accurate method for positioning. The most important challenge of this method is senility to initial point; this problem is solved in positioning based on factor graphs. So, in this paper, first positioning equations using angle of arrival is considered based on factor graphs algorithm. Second, final location estimation is performed using Gauss Newton algorithm with error near to Cramer-Rao bound Simulation results shows that positioning error using two step method has maximum 6% gap to Cramer-Rao Bound.

机译：本文提出了一种基于高斯 - 牛顿和因子图算法的步骤方法，以提高本地化的准确性。高斯 - 牛顿算法是定位的准确方法。这种方法最重要的挑战是敏锐性的初始点;基于因子图的定位解决了这个问题。因此，在本文中，基于因子图算法考虑使用到达角度的第一定位方程。其次，使用Gause Newton算法使用靠近Cramer-Rao绑定仿真结果来执行最终位置估计结果表明，使用两步法的定位误差最大为克拉姆 - Rao绑定的6％。

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《International Computer Conference》|2009年||共5页
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Behzad Omidali; S. Ali-Asghar Beheshti Shirazi;
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中图分类 TP3-53;
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4. Performance improvement of AOA positioning using a two-step plan based on factor graphs and the gauss-newton method [C] . Omidali B., Shirazi S. Computer Conference, 2009. CSICC 2009 . 2009

机译：基于因子图和高斯-牛顿法的两步计划提高了AOA定位的性能
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Performance Improvement of AOA Positioning using A Two-Step Plan Based on Factor Graphs and the Gauss-Newton Method

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