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Published： 07 October 2022 ，
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郑元勋，李清华，王常虹，黄远，钟佳朋.2022.基于多磁信标的指纹匹配定位算法.遥感学报，26（10）： 2073-2082
Zheng Y X，Li Q H，Wang C C，Huang Y and Zhong J P. 2022. Accurate navigation and positioning method based on magnetic beacon. National Remote Sensing Bulletin， 26（10）：2073-2082
针对室内、地下以及障碍物较多的复杂环境中，可用导航源匮乏问题，本文提出一种利用低频时变磁场实现目标高精度位置与姿态解算的解决方案。传统时变磁场定位方法要求磁信标坐标系与目标坐标系一致且无法解算目标相对姿态角信息，同时精度普遍较差。本文提出的方案在解决传统方案的局限性基础上，又提出一种基于指纹匹配的改进方案，具有穿透性好、鲁棒性强且精度高的特点。首先根据空间中测量磁场计算磁信标接收信号强度RSSI（Received Signal Strength Indicator）拟合直线，根据指纹匹配原理估计目标位置；再根据测量磁场方向矢量模型，反演解算目标姿态角信息，实现目标位置与姿态信息解算过程，研究并分析了磁信标导航系统误差来源及解决方案；最后通过对比实验，验证本文提出的算法在实验条件下，位置估计误差期望为0.069 m，姿态角估计误差期望为2.3°，且误差不随时间积累，相对于传统的磁信标导航方案具有明显优势，具有较高的工程应用价值。
To solve the problem of lacking a reliable positioning source in complex environments such as indoor and underground
a high-precision position and attitude estimation method based on the low-frequency time-varying magnetic field is proposed in this paper. The traditional time-varying magnetic field positioning method requires the magnetic beacon coordinate system to be consistent with the target
which cannot solve the relative attitude angle information of the target and the accuracy is poor. The proposed method realized with the fingerprint matching algorithm overcomes the shortcoming of traditional solutions
which is penetrating
robust
and accurate.
According to the Biot–Savart Law
the magnetic field intensity decays with the distance between the target and the magnetic source
and the orientation of the measured magnetic field has a certain relation to orientation from the source to the target. Hence
according to this principle
an improved fingerprint algorithm is introduced. Firstly
the RSSI fitting line of the magnetic beacon is calculated according to the measured magnetic field in space
and the position is estimated by the fingerprint matching algorithm. The attitude can be achieved from the estimated position and magnetic field direction vector model. Furthermore
the disturbing factors of the magnetic beacon positioning system are analyzed and the optimization method is approached to improve system performance.
The performance includes the effective distance of a single magnetic beacon
the positioning accuracy
the stability of the proposed approach
and the influence of the magnetic beacon number are verified by the experiment. The effective distance of a single magnetic beacon is 14 m. The result exhibits the positioning error expectation is 0.069 m and attitude error expectation is 2.3°
respectively. The error does not accumulate over time
which has obvious advantages over the traditional magnetic beacon navigation solutions and has high engineering application value.
位姿解算磁信标模型地下与室内导航指纹匹配算法
position and attitude estimationmodel of magnetic beaconunderground and indoor navigationfingerprint matching algorithm
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