| 一种基于行人航位推算的改进航迹跟踪算法 |
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| 引用本文： | 胡锐,吴飞,通雁辉,朱海,鄢松,陆雯霞.一种基于行人航位推算的改进航迹跟踪算法[J].大地测量与地球动力学,2021,41(1):49-55. |
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| 作者姓名： | 胡锐 吴飞 通雁辉 朱海 鄢松 陆雯霞 |
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| 作者单位： | 上海工程技术大学电子电气工程学院,上海市龙腾路333号,201620;上海工程技术大学电子电气工程学院,上海市龙腾路333号,201620;上海工程技术大学电子电气工程学院,上海市龙腾路333号,201620;上海工程技术大学电子电气工程学院,上海市龙腾路333号,201620;上海工程技术大学电子电气工程学院,上海市龙腾路333号,201620;上海工程技术大学电子电气工程学院,上海市龙腾路333号,201620 |
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| 基金项目： | 国家自然科学基金;上海市科学技术委员会项目;上海市"扬帆计划" |
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| 摘 要： | 针对在未知环境中行人轨迹跟踪问题，提出一种基于行人航位推算的改进航迹跟踪算法，有效实现了在磁场干扰环境下行人轨迹的高精确跟踪。在步数估计中，利用双重阈值二值化算法对加速度数据进行分析，进而获得行人的运动步数；在航向估计中，利用自适应融合算法来获取航向。该融合过程首先根据姿态更新微分方程，将角速度与加速度融合获取一次航向角，再通过磁感应强度阈值确定一次航向角与磁力计测算航向角融合的权重，最后通过实验验证算法的有效性和优越性。结果表明，在未知环境中行走32 m的距离，获得的轨迹跟踪误差小于1.1%，定位误差小于0.75 m和1 m的概率分别为59%和80%，显著优于对比算法。
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| 关 键 词： | 行人航位推算 智能手机 磁干扰 双重阈值二值化 自适应融合 |
Improved Trajectory Tracking Algorithm Based on Pedestrian Dead Reckoning |
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| HU Rui,WU Fei,TONG Yanhui,ZHU Hai,YAN Song,LU Wenxia.Improved Trajectory Tracking Algorithm Based on Pedestrian Dead Reckoning[J].Journal of Geodesy and Geodynamics,2021,41(1):49-55. |
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| Authors: | HU Rui WU Fei TONG Yanhui ZHU Hai YAN Song LU Wenxia |
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| Institution: | (College of Electronic and Electronic Engineering,Shanghai University of Engineering Science,333 Longteng Road,Shanghai 201620,China) |
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| Abstract: | Aiming at the problem of pedestrian trajectory tracking in an unknown environment, to achieve accurate tracking in the magnetic field, we propose an improved trajectory tracking algorithm based on pedestrian dead reckoning. We use a double threshold binarization algorithm to analyze the acceleration data in step estimation, and an adaptive fusion algorithm is proposed in course estimation. This fusion algorithm fuses the angular velocity and acceleration to obtain a heading angle based on the updating differential equation, and then determines the weight of the heading angle and the magnetometer to measure the heading fusion through the magnetic induction intensity threshold. The effectiveness and superiority of the proposed algorithm are validated by an experiment. The experimental results show that the trajectory error obtained by the proposed tracking algorithm is less than 1.1% when the total walk distance is 32 m, and the probability that the positioning error is less than 0.75 m and 1 m is 59% and 80%, which effectively verifies its excellence. |
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| Keywords: | pedestrian dead reckoning smart phone magnetic interference double threshold binarization adaptive fusion |
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