智能移动终端室内异步声音定位方法

张磊; 刘江; 冯雪; 屈秉男; 何为; 胡志新

doi:10.7652/xjtuxb202309014

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智能移动终端室内异步声音定位方法

—————————————————————— | 更新时间：2025-07-09

- 智能移动终端室内异步声音定位方法
- Indoor Acoustic Asynchronous Positioning for Smart Mobile Devices
- 西安交通大学学报 2023年57卷第9期页码：133-143
- 作者机构：
  
  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
- 作者简介：
  
  : 2022-12-08。作者简介: 张磊(1985—),男,博士,讲师
  胡志新(通信作者),男,副教授。基金项目: 国家自然科学基金资助项目(62003503)
- 基金信息：
  
  : 2022-12-08。作者简介: 张磊(1985—),男,博士,讲师;胡志新(通信作者),男,副教授。基金项目: 国家自然科学基金资助项目(62003503);陕西省自然科学基金资助项目(2020JQ-389)。
- DOI：10.7652/xjtuxb202309014
  中图分类号： TN912.3
- 网络首发：2023-09-10，
  
  纸质出版：2023
- 稿件说明：
移动端阅览
张磊, 刘江, 冯雪, 等. 智能移动终端室内异步声音定位方法[J]. 西安交通大学学报, 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.
张磊, 刘江, 冯雪, 等. 智能移动终端室内异步声音定位方法[J]. 西安交通大学学报, 2023,57(9):133-143. DOI： 10.7652/xjtuxb202309014.

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.

摘要

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。

Abstract

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.

关键词

Keywords

references

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