| 基于小波和RBF神经网络的多传感器时间对准算法研究 |
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| 引用本文： | 邓捷,陆百川,马庆禄,刘权富.基于小波和RBF神经网络的多传感器时间对准算法研究[J].交通科技与经济,2014(1):30-34. |
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| 作者姓名： | 邓捷 陆百川 马庆禄 刘权富 |
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| 作者单位： | [1]重庆交通大学交通运输学院,重庆400074 [2]重庆山地城市交通系统与安全实验室,重庆400074 |
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| 基金项目： | 国家山区公路工程技术研究中心开放基金（gsgzj-2012-08）,重庆市教委科学技术研究项目（KJl30423） |
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| 摘 要： | 提出利用小波降噪和RBF神经网络进行时间对准算法,该方法先对采集到的数据进行降噪处理,为下一步操作提供准确数据;然后利用RBF神经网络将不同传感器采集不同采样周期的数据对应到同一个时间点上,进行多传感器时间对准,为后面数据特征提取和数据融合提供高精度数据支持。通过仿真结果与其它方法的对比可得该方法运算速度快,具有数据修正能力和精确度高的特点,适用于多传感器的时间对准。
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| 关 键 词： | 小波降噪 RBF神经网络 时间对准 多传感器 |
Algorithm of Alignment of Multi-Sensor Time Based on Wavelet and RBF Neural Network |
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| DENG Jie,LU Bai-chuan,MA Qing lu,LIU Quan fu.Algorithm of Alignment of Multi-Sensor Time Based on Wavelet and RBF Neural Network[J].Technology & Economy in Areas of Communications,2014(1):30-34. |
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| Authors: | DENG Jie LU Bai-chuan MA Qing lu LIU Quan fu |
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| Institution: | 1. School of Traffic ＆ Transportation, Chongqing Jiaotong University, Chongqing 400074, China; 2. Key Lab of Traffic System ＆ Safety in Mountain Cities, Chongqing 400074, China) |
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| Abstract: | It proposed the use of wavelet reduces noise and RBF neural network for time alignment algorithm, first, this way can reduce the collected noise of data, as providing accurate data to next step; and then sampling period corresponds to the same point in time of different sensors collect data by RBF neural different networks, to the back data feature extraction and data fusion to provide high-precision data support by multi-sensor time alignment. The simulation results compared with other methods, the method computing is speeder, capacity of correcting data and higher accuracy, suitable for multi-sensor time alignment. |
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| Keywords: | wavelet noise reduction RBF neural network time alignment multi-sensor |
| 本文献已被 CNKI 维普 等数据库收录！ |
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