基于改进Chan-Taylor算法的震后定位搜索技术研究

胡喆馨; 卜凡亮; 王媛媛

doi:10.11899/zzfy20230119

基于改进Chan-Taylor算法的震后定位搜索技术研究

doi: 10.11899/zzfy20230119

中国人民公安大学, 信息网络安全学院, 北京 100032

详细信息

作者简介:
胡喆馨，女，生于1997年。硕士研究生。主要从事安全防范技术与工程研究。E-mail：619631920@qq.com

通讯作者:
卜凡亮，男，生于1965年。教授。主要从事安全防范技术与工程研究。E-mail：bufanliang@sina.com

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出版历程
- 收稿日期: 2022-02-15
- 刊出日期: 2023-03-31

Research on the Post-earthquake Localization Search Technology Based on the Improved Chan-Taylor Algorithm

College of Information Technology and Internet Security, People’s Public Security University of China, Beijing 100032, China

摘要

摘要: 针对震后复杂的非视距传播环境，在充分了解废墟状态下信道特征和信号传播特点的基础上，构建震后无线定位系统框架，提出改进的Chan-Taylor位置解算方法，将改进的残差加权算法与多元泰勒级数展开算法相融合，并进行二次残差加权。对废墟环境进行实地调研，并通过Matlab进行仿真模拟实验，仿真结果表明，改进后的算法能更好地抑制非视距环境下TDOA的测量误差，对震后被压埋幸存者的位置解算与及时营救具有重要意义。
- 震后定位搜救 /
- 残差加权算法 /
- Taylor算法 /
- 到达时间差
Abstract: For the complex non-line-of-sight propagation environment after the earthquake, based on the understanding of the channel characteristics and signal communication characteristics, the post-earthquake wireless positioning system framework is constructed, and the improved Chan-Taylor position solution is proposed, integrating the improved residual weighting algorithm with the multivariate Taylor series expansion algorithm, and performing quadratic residual weighting. After the field investigation of the ruins environment, and simulation experiments using the Matlab software, the simulation results show that the improved algorithm can better suppress the measurement error of TDOA in the non-line-of-sight environment, which has great significance for the location calculation and timely rescue of victims buried after the earthquake.
- Post-earthquake localization search and rescue /
- Residual weighted algorithm /
- Taylor algorithm /
- TDOA

HTML全文

图 1 定位搜救系统流程

Figure 1. The process of localization search and rescue system

下载: 全尺寸图片幻灯片

图 2 目标估计位置分布情况

Figure 2. Localization distribution of target estimation

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图 3 定位误差累计分布曲线

Figure 3. Localization error cumulative distribution curve

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图 4 定位测试场景

Figure 4. The test scenario of localization

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图 5 定位误差随基站个数的变化

Figure 5. Localization error varies with the number of base stations

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表 1 不同信道环境下的参数取值

Table 1. Parameters for different channel environments

信道环境	T/ μs
远郊地区	0.10
一般市区	0.40
典型城区	0.98
恶劣城区	2.53
丘陵地区	6.88

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表 2 均方根误差对比

Table 2. Comparison of the root mean squared error

项目	算　法
项目	Chan	Taylor	Chan-Taylor	改进的 Chan-Taylor
均方根误差	8.351	7.479	5.982	3.556
误差平均值	2.845	2.439	1.876	1.372

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表 3 不同定位算法的运行时间

Table 3. Running time of the different localization algorithms

项目	算法
项目	Chan	Taylor	Chan-Taylor	改进的Chan-Taylor
4个基站参与定位运行时间/s	1.069	1.454	1.646	1.652
5个基站参与定位运行时间/s	1.097	1.510	1.722	1.715
6个基站参与定位运行时间/s	1.131	1.612	1.898	1.919

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