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A novel vehicle dynamics identification method utilizing MIMU sensors based on support vector machine

机译:基于支持向量机的MIMU传感器车辆动力学识别方法

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The major challenge of inertial navigation system (INS) is the rapid navigation error drift when aiding sensors are unavailable. However, if the dynamics of land vehicle can be detected, these errors can be corrected or restrained. A method based on support vector machine (SVM) using the outputs of MIMU is proposed here to identify the dynamics of land vehicle. This method computes part of the time-domain features and frequency-domain features. Then, a subset of these features is selected based on wrapper evaluation criteria. Afterwards, SVM is trained based on these selected features. Finally, the trained SVM is used in identification tests. The identification results show that this method can correctly identify the stationary, straight-line and cornering states.
机译:惯性导航系统(INS)的主要挑战是在辅助传感器不可用时快速的导航误差漂移。但是,如果可以检测到陆地车辆的动态,则可以纠正或限制这些错误。本文提出了一种基于支持向量机(SVM)的方法,该方法利用MIMU的输出来识别陆地车辆的动力学特性。该方法计算时域特征和频域特征的一部分。然后,基于包装程序评估标准选择这些功能的子集。之后,将基于这些选定功能对SVM进行培训。最后,训练有素的SVM用于识别测试。识别结果表明,该方法可以正确识别静止,直线和转弯状态。

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