A Human-Body Local Specific Absorption Rate Evaluation Algorithm in Indoor Complex Electromagnetic Environments

LIU Zicheng; CAO Miao; WANG Shilong; ZONG Yali; LI Changyou

doi:10.12263/DZXB.20250330

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A Human-Body Local Specific Absorption Rate Evaluation Algorithm in Indoor Complex Electromagnetic Environments

PAPERS | 更新时间：2026-05-28

- A Human-Body Local Specific Absorption Rate Evaluation Algorithm in Indoor Complex Electromagnetic Environments
- ACTA ELECTRONICA SINICA Vol. 54, Issue 2, Pages: 611-622(2026)
- 作者机构：
  
  西北工业大学电子信息学院，陕西西安 710072
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(62201469)
- DOI：10.12263/DZXB.20250330
  CLC： TN959.5;
- Received：25 April 2025，
  
  Accepted：09 February 2026，
  
  Published：25 February 2026
- 稿件说明：
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刘自成, 曹苗, 王士龙, 等. 室内复杂电磁环境下人体局部比吸收率评估方法[J]. 电子学报, 2026, 54(02): 611-622.

LIU Zicheng, CAO Miao, WANG Shilong, et al. A Human-Body Local Specific Absorption Rate Evaluation Algorithm in Indoor Complex Electromagnetic Environments[J]. Acta Electronica Sinica, 2026, 54(02): 611-622.
刘自成, 曹苗, 王士龙, 等. 室内复杂电磁环境下人体局部比吸收率评估方法[J]. 电子学报, 2026, 54(02): 611-622. DOI：10.12263/DZXB.20250330

LIU Zicheng, CAO Miao, WANG Shilong, et al. A Human-Body Local Specific Absorption Rate Evaluation Algorithm in Indoor Complex Electromagnetic Environments[J]. Acta Electronica Sinica, 2026, 54(02): 611-622. DOI：10.12263/DZXB.20250330

摘要

随着现代社会无线通信技术的飞速发展，智能手机、笔记本电脑及Wi-Fi路由器等无线设备已成为室内环境不可或缺的一部分。由于现代人约80%~90%的时间处于室内，室内多径效应导致的复杂电磁环境对人体电磁暴露剂量的准确评估构成了巨大挑战。传统的物理测量法受限于空间采样点且难以应对人体位置的随机性，而全波仿真算法虽然精度高，但面对大规模室内场景时计算资源消耗极大，难以实现实时预测。针对这一现状，本文提出了一种基于混沌多项式展开法（Polynomial Chaos Expansion，PCE）的室内人体局部比吸收率（Specific Absorption Rate，SAR）峰值快速预测模型构建方法。本研究首先利用射线追踪法（Ray-Tracing）对室内复杂电磁环境进行数字化重建。通过追踪射线在室内各表面间的反射、绕射及散射路径，准确获取了人体所处位置周围的电磁场分布。为了解决大规模环境仿真与精细人体模型耦合的矛盾，本文引入惠更斯法则，将复杂的室内背景场转化为人体周围的等效辐射源（即惠更斯盒子）。随后，结合时域有限差分法（Finite-Difference Time-Domain，FDTD）模拟等效辐射源与高分辨率数字人体模型的近场耦合效应，精准计算人体内部的电场强度分布及局部SAR峰值，从而生成涵盖不同暴露场景的高质量训练数据集。在模型构建阶段，本文采用了稀疏混沌多项式展开法，通过对不确定性输入变量（如无线设备位置、人体位置等）进行正交多项式基函数展开，建立了输入变量与SAR峰值之间的显式解析映射关系。该方法通过稀疏化技术有效缓解了“维数灾难”问题，极大提升了建模效率。研究结果表明，本文所采用的室内复杂电磁环境重建方法具有极高的准确性。通过实验对比验证，重建环境与实测结果的相对误差小于5%，确保了电磁暴露场景的真实性。此外，基于PCE建立的预测模型在测试集上的预测精度

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2.96333337

2.53999996

0.9，且预测效率达到了毫秒量级，相比传统的全波电磁仿真算法，计算速度实现了跨越式的提升。综上所述，本文提出的局部SAR快速评估方法不仅克服了室内复杂环境下人体暴露剂量难以量化的难题，还解决了计算效率与精度之间的平衡问题。该研究为实现密闭环境下电磁辐射剂量的实时监测奠定了理论基础，并为室内无线通信设备的安全使用及复杂电磁环境下的公共安全管理决策提供了关键的技术支撑。

Abstract

Modern individuals spend a significant portion of their daily lives in indoor environments. However

the inherent multipath effects in these settings create complex electromagnetic environments

posing a major challenge for the accurate assessment of human electromagnetic exposure doses from indoor wireless devices. Traditional physical measurement methods are often restricted by limited spatial sampling points and struggle to account for the uncertainty of radiation source locations and human positions. Furthermore

while full-wave simulation algorithms provide high accuracy

they require immense computational resources for large indoor scenes

making real-time prediction difficult. To address these challenges

this paper proposes a rapid prediction model for human-body local specific absorption rate (SAR) peaks based on the sparse polynomial chaos expansion (PCE) method. The research first utilizes the ray-tracing method to achieve precise reconstruction of complex indoor electromagnetic environments. By tracing the paths of electromagnetic waves as they undergo reflection

diffraction

and scattering off various indoor surfaces

the electromagnetic field distribution surrounding the human body is accurately obtained. To bridge the gap between large-scale environmental simulation and fine-grained human-body modeling

the study applies Huygens

’ principle to derive equivalent radiation sources (Huygens’ boxes) of the incident field on the human body. Subsequently

the finite-difference time-domain (FDTD) method is integrated to simulate the coupling effects between the electromagnetic environment and the digital human model. This process calculates the internal electric field distribution and 1 g SAR peaks across various tissues

forming a high-quality training dataset. In the model construction phase

a sparse PCE model is established to map the relationship between uncertain input variables—such as wireless device and human body coordinates and the resulting SAR peaks. By employing an orthogonal matching pursuit (OMP) algorithm

the model identifies the most significant expansion bases

effectively mitigating the “curse of dimensionality” and preventing overfitting even with small sample sizes. Additionally

variable transformations are introduced to convert absolute coordinates into relative distances and angles

significantly enhancing the model’s predictive capability. The experimental results demonstrate that the reconstructed indoor electromagnetic environment is highly accurate

with a relative error of less than 5% compared to experimental measurements. The sparse PCE prediction model achieves a high accuracy with a determination coefficient

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=109257118&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=109257097&type=

2.96333337

2.53999996

0.9. Critically

the prediction efficiency reaches the millisecond level

representing a transformative

increase in speed compared to traditional full-wave electromagnetic simulations. Furthermore

sensitivity analysis using Sobol’s method reveals that the relative distance between the wireless device and the human body is the dominant factor influencing the SAR peak. In conclusion

the proposed rapid SAR estimation method establishes a closed-loop link between “Electromagnetic Environment”

“Human Radiation Dose”

“Prediction Model”

and “Sensitivity Analysis”. This work lays the theoretical foundation for the real-time measurement of electromagnetic radiation doses in enclosed environments and provides vital technical support for safety management and decision-making regarding indoor wireless communication devices.

关键词

Keywords

references

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