基于扩展卡尔曼滤波的高程估计算法
发布时间：2018-09-05 20:04
【摘要】：在室内行人定位系统中,行人的高程定位精度关系到整个定位系统的可靠性。提出一种基于腰间传感器的室内行人高程估计算法。首先利用支持向量机识别行人上楼下楼动作,针对行人的运动状态采用自适应的高程估计算法。针对气压计测量值易受环境影响的问题,采用了基于EKF融合气压和加速度的高度估计算法,提高了高度估计算法的稳定性。经实验验证,当室内人员进行平地走、上楼等一连串动作后,基于差分气压测高法计算的高度误差为9.92%,基于加速度估计的行人高度误差为9.52%,EKF融合后定位误差下降到2.32%,提高了高程估计的精度。
[Abstract]:In indoor pedestrian positioning system, the accuracy of pedestrian elevation location is related to the reliability of the whole positioning system. An indoor pedestrian elevation estimation algorithm based on waist sensor is proposed. Firstly, support vector machine (SVM) is used to identify the movement of pedestrians upstairs and downstairs, and an adaptive elevation estimation algorithm is used to estimate the motion state of pedestrians. Aiming at the problem that barometer measurements are easily affected by environment, a height estimation algorithm based on EKF fusion of pressure and acceleration is adopted to improve the stability of the height estimation algorithm. After a series of actions, such as walking flat on the ground, going upstairs and so on, The height error calculated by differential pressure altimetry is 9.92, and the error of pedestrian height based on acceleration estimation is 9.52EKF. The positioning error is reduced to 2.32 after fusion, which improves the accuracy of elevation estimation.
【作者单位】： 上海大学通信与信息工程学院;中国科学院上海高等研究院;
【基金】：十三五国家重点研发计划(2016YFC0801505)资助
【分类号】：TN713;TP212
本文编号：2225326
[Abstract]:In indoor pedestrian positioning system, the accuracy of pedestrian elevation location is related to the reliability of the whole positioning system. An indoor pedestrian elevation estimation algorithm based on waist sensor is proposed. Firstly, support vector machine (SVM) is used to identify the movement of pedestrians upstairs and downstairs, and an adaptive elevation estimation algorithm is used to estimate the motion state of pedestrians. Aiming at the problem that barometer measurements are easily affected by environment, a height estimation algorithm based on EKF fusion of pressure and acceleration is adopted to improve the stability of the height estimation algorithm. After a series of actions, such as walking flat on the ground, going upstairs and so on, The height error calculated by differential pressure altimetry is 9.92, and the error of pedestrian height based on acceleration estimation is 9.52EKF. The positioning error is reduced to 2.32 after fusion, which improves the accuracy of elevation estimation.
【作者单位】： 上海大学通信与信息工程学院;中国科学院上海高等研究院;
【基金】：十三五国家重点研发计划(2016YFC0801505)资助
【分类号】：TN713;TP212
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