| 基于遗传神经网络的AOA跟踪算法 |
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| 引用本文： | 谢川,毛永毅.基于遗传神经网络的AOA跟踪算法[J].电子科技,2014,27(11):8-10,13. |
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| 作者姓名： | 谢川 毛永毅 |
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| 作者单位： | (1.西安邮电大学 通信与信息工程学院,陕西 西安 710061;2.西安邮电大学 研究生学院,陕西 西安 710061) |
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| 基金项目： | 陕西省自然科学基金资助项目，陕西省教育厅专项科研基金资助项目 |
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| 摘 要： | 提出了一种在非视距传播环境中基于遗传神经网络的到达角定位跟踪算法。首先使用遗传算法优化后向传播神经网络的初始权值,将优化后的GA-BP神经网络对AOA测量值进行修正,用最小二乘算法确定移动台的位置,再用卡尔曼滤波器配合相关检测距离门对移动台实施跟踪。仿真结果表明,该算法能有效地实现移动台的动态跟踪,且性能优于传统BP神经网络和LS算法。
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| 关 键 词： | 跟踪算法 遗传算法 神经网络 卡尔曼滤波器 到达角度差 |
AOA Tracking Algorithm Based on Genetic Neural Network |
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| XIE Chuan
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MAO Yongyi.AOA Tracking Algorithm Based on Genetic Neural Network[J].Electronic Science and Technology,2014,27(11):8-10,13. |
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| Authors: | XIE Chuan MAO Yongyi |
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| Affiliation: | (1.School of Communication and Information Engineering,Xi'an University of Posts and Telecommunications,Xi'an 710061,China;
2.Postgraduate School,Xi'an University of Posts and Telecommunications,Xi'an 710061,China) |
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| Abstract: | An Angel of Arrival（ AOA） tracking algorithm based on genetic neural network is proposed in this paper. The genetic algorithm is able to correct the initial weights of Back Propagation（ BP） neural network and then the Non-Line-Of-Sight（ NLOS） errors can be corrected by the optimized GA-BP neural network. Furthermore,the positions of Moblie Station（ MS） can be estimated by Least-Square（ LS） algorithm combined with correlation detection gate,and the MS is tracked by the Kalman filter. The simulation results show that the algorithm performance is better than traditional BP neural network and LS algorithm in the dynamic state. |
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| Keywords: | tracking algorithm genetic algorithm neural network kalman filter angel of arrival |
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