震后特殊环境下压埋人员精确定位算法

成鹏; 肖东升

doi:10.11899/zzfy20240119

震后特殊环境下压埋人员精确定位算法

doi: 10.11899/zzfy20240119

成鹏^1,,
肖东升^{1, 2, ,}

1.
西南石油大学，土木工程与测绘学院, 成都 610500
2.
西南石油大学，测绘遥感地理信息防灾应急研究中心, 成都 610500

基金项目: 国家自然科学基金（51774250）；西南石油大学测绘遥感地信与防灾应急青年科技创新团队（2019CXTD07）；四川省区域创新合作项目

详细信息

作者简介:
成鹏，男，生于1998年。硕士研究生。主要从事地震压埋人员的定位研究。E-mail：1784262989@qq.com

通讯作者:
肖东升，男，生于1974年。博士，教授。主要从事地震压埋人员定位与防灾减灾技术研究。E-mail：xiaodsxds@163.com

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出版历程
- 收稿日期: 2022-08-04
- 刊出日期: 2024-03-31

Algorithm of Accurate Location of Buried Personnel in Special Environment after Earthquake

Cheng Peng^1
,,
Xiao Dongsheng^{1, 2
, ,}

1.
School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China
2.
Surveying, Mapping and Remote Sensing Geographic Information Disaster Prevention and Emergency Research Center, Southwest Petroleum University, Chengdu 610500, China

摘要

摘要: 针对目前对震后压埋人员定位精度较低、探测设备成本高且易受环境影响等不足，提出适用于压埋环境特性的压埋人员手机WiFi定位方法，通过衰减因子模型对WiFi探针获取的RSSI数据进行距离解算，结合简化压埋环境内部信号传输方式，采用高斯-卡尔曼滤波对获取的RSSI数据进行处理，通过模型测定的距离，利用改进附有参数的加权最小二乘平差方法，结合粒子群优化算法，最终得到压埋人员手机平面坐标位置。研究结果表明，该方法具有较高精度，在10 m×10 m范围内其平面坐标定位误差在0.3 m左右，可为震后压埋人员应急救援提供辅助决策。
- 压埋环境 /
- 衰减因子模型 /
- 压埋人员定位 /
- 高斯-卡尔曼滤波 /
- 粒子群优化算法
Abstract: In view of the current shortcomings of the positioning accuracy of the buried people after the earthquake, the high cost of the detection equipment and the vulnerability to environmental impact, in this paper we propose a WiFi Positioning Method to search for the buried people's mobile phones, which is suitable for the characteristics of the signals from buried environment. The RSSI data obtained by the WiFi probe is calculated by the attenuation factor model. Combined with the simplified internal signal transmission mode of the buried environment, the obtained RSSI data is processed by Gauss Kalman filter. Through the distance measured by the model, using the improved weighted least square adjustment method with parameters, combined with particle swarm optimization algorithm, it is capab le to obtain the plane coordinate position of the buried personnel's mobile phone.The experimental results show that this method has high accuracy, with the average error of plane coordinate positioning about 0.3 m within the range of 10 m × 10 m, which can provide auxiliary decision-making for emergency rescue of buried personnel after earthquake.
- Buried environment /
- Attenuation factor model /
- Positioning of embedded personnel /
- Gaussian Kalman filter /
- Particle swarm optimization algorithm

HTML全文

图 1 压埋环境示意

Figure 1. Schematic diagram of buried environment

下载: 全尺寸图片幻灯片

图 2 压埋信号传输路径

Figure 2. Transmission path of buried signal

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图 3 数学关系

Figure 3. Mathematical relation diagram

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图 4 多组WiFi探针的布设方式

Figure 4. Layout of multiple groups of WiFi probes

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图 5 滤波性能比较

Figure 5. Comparison of filtering performance

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图 6 不同滤波测距误差

Figure 6. Ranging error of different filters

下载: 全尺寸图片幻灯片

表 1 模拟压埋环境下平面坐标定位结果（单位：米）

Table 1. Results of plane positioning in simulated buried environment（Unit：m）

点号	方案1			方案2
点号	定位结果	测距中误差	定位误差	定位结果	测距中误差	定位误差	真实位置
P1	(4.86,1.79)	1.63	3.21	(5.18,4.86)	0.25	0.23	(5,5)
P2	(5.21,0.58)	2.3	3.51	(6.14,4.21)	0.32	0.25	(6,4)
P3	(5.42,4.37)	2.8	1.73	(6.28,5.84)	0.54	0.32	(6,6)
P4	(3.80,3.42)	2.5	2.59	(4.51,5.86)	0.43	0.53	(4,6)

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