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    曾凡仔 梁振华 李仁发. 一种基于支撑向量回归与博弈论的移动位置跟踪算法[J]. 计算机研究与发展, 2010, 47(10): 1709-1713.
    引用本文: 曾凡仔 梁振华 李仁发. 一种基于支撑向量回归与博弈论的移动位置跟踪算法[J]. 计算机研究与发展, 2010, 47(10): 1709-1713.
    Zeng Fanzi, Liang Zhenhua, and Li Renfa. An Approach to Mobile Position Tracking Based on Support Vector Regression and Game Theory[J]. Journal of Computer Research and Development, 2010, 47(10): 1709-1713.
    Citation: Zeng Fanzi, Liang Zhenhua, and Li Renfa. An Approach to Mobile Position Tracking Based on Support Vector Regression and Game Theory[J]. Journal of Computer Research and Development, 2010, 47(10): 1709-1713.

    一种基于支撑向量回归与博弈论的移动位置跟踪算法

    An Approach to Mobile Position Tracking Based on Support Vector Regression and Game Theory

    • 摘要: 非视距传输造成测距严重有偏,从而使得位置估计误差显著增加.将定位问题嵌入到机器学习框架,并通过引入博弈理论对位置估计进行平滑来实现移动位置跟踪.由于将观测作为射频特征,而不是实际距离的度量,因此能够大大减轻非视距传输对位置估计性能的影响,同时在平滑过程中,将噪声建模为估计子的对手,通过微分博弈理论来实现平滑,并与卡尔曼滤波平滑进行了比较.仿真实验表明,方法具有更好的位置估计性能,特别是在非视距环境下其效果更为明显.

       

      Abstract: The location service is foundation of pervasive computing, intelligent transportation and application of WSN, so the wireless positioning is the focus of the current research. Current location techniques include ToA, TDoA and RSSI. And considering that non-line-of-sight propagation introduces the significant bias in measurements and thus the very large error in current location estimation technique, a two-step position tracking scheme is proposed to mitigate the position tracking error. In this scheme, an SVR model of node position with radio parameters is firstly established by supervising learning. Then the position estimation from SVR model is smoothed by the game. Because the radio parameter is not considered as the distance measure, but as the feature to train the SVR model, the side effect of non-line-of-sight is mitigated. And by modeling the noise as the adversary of position estimator, a position smooth method based on game theory is introduced. Because of its ability to handle the uncertain and unmodeled noise, game theory can attain in theory more accuracy of position tracking compared with Kalman-filter, which can only deal with the Gaussian noise. Simulations show that the scheme proposed results in the more accurate performance of location estimation, especially in the harsh environment.

       

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