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1. 长安大学工程机械学院,西安,710064
2. 西安现代控制技术研究所,西安,710065
3. 中国科学院上海微系统与信息技术研究所,上海,201800
Online First:10 September 2023,
Published:2023
移动端阅览
ZHANG Lei, LIU Jiang, FENG Xue, et al. Indoor Acoustic Asynchronous Positioning for Smart Mobile Devices[J]. 2023, 57(9): 133-143.
ZHANG Lei, LIU Jiang, FENG Xue, et al. Indoor Acoustic Asynchronous Positioning for Smart Mobile Devices[J]. 2023, 57(9): 133-143. DOI: 10.7652/xjtuxb202309014.
针对智能移动终端的高精度室内定位需求
提出一种基于到达时间差和相对运动速度信息的异步声音定位方法。首先
结合距离差和相对运动速度量测
建立短时位置序列的联合估计模型
来降低速度积分所引入的累积误差; 然后
基于LM(Levenberg-Marquardt)算法
对所建立的模型进行快速求解; 最后
设计了一种迭代优化过程
对短时位置序列的帧前位置施加随机扰动
降低初始位置对定位结果的影响
在低基站部署密度下
实现智能移动终端高精度的室内异步声音定位。对比数值仿真和实验结果表明:在二维和三维定位场景下
所提出方法均优于传统异步定位方法
具有更高的定位精度和稳定性
并将定位所需的最少基站数量分别减少至2个和3个; 随着基站数量的增加
传统异步定位方法逐渐接近所提出方法的定位性能; 在二维场景的3基站部署条件下
当短时位置序列长度T=2时
所提出方法的定位精度有90%的概率优于0.43 m
而当T=3时为0.29 m。因此
该方法能够在低基站部署密度环境中实现高精度的位置估计
同时具有较好的定位稳定性。
Aiming to meet the requirement of highly accurate indoor positioning for smart mobile devices
a novel acoustic asynchronous positioning method was proposed in this paper based on distance difference and relative velocity measurements. First
combining the measurements of distance difference and relative velocity
a joint estimation model of short time position sequence was established to reduce the cumulative error caused by velocity integration. Then
the LM(Levenberg-Marquardt)algorithm was used to quickly solve the established model. Finally
an iterative optimization process was designed to apply random perturbations to the pre-frame position of the short time position sequence to mitigate the impact of the initial position on the positioning results. Through those methods
accurate indoor acoustic asynchronous positioning can be realized for smart mobile devices under the low density of beacon deployment. The numerical simulation and experimental results show: The proposed method is superior to traditional asynchronous positioning methods in both 2D and 3D positioning scenarios
with higher positioning accuracy and stability and the minimum number of required beacons being reduced to 2 and 3
respectively; the positioning performance of the traditional asynchronous positioning methods gradually approach that of the proposed method as the number of beacons increases; in a 2D positioning scenario with 3 beacons
the positioning accuracy of the proposed method is better than 0.43 m with a 90% probability when the length of the short time position sequence T=2
and better than 0.29 m when T=3. Therefore
the proposed method can achieve both higher positioning accuracy and better positioning stability in conditions with a low beacon deployment density.
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