室内复杂电磁环境下人体局部比吸收率评估方法OA

Modern individuals spend a significant portion of their daily lives in indoor environments.However,the in⁃herent multipath effects in these settings create complex electromagnetic environments,posing a major challenge for the ac⁃curate assessment of human electromagnetic exposure doses from indoor wireless devices.Traditional physical measure⁃ment 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 re⁃quire immense computational resources for large indoor scenes,making real-time prediction difficult.To address these chal⁃lenges,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 un⁃dergo 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 hu⁃man-body modeling,the study applies Huygens'principle to derive equivalent radiation sources(Huygens'boxes)of the in⁃cident 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 inter⁃nal 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 wire⁃less device and human body coordinates and the resulting SAR peaks.By employing an orthogonal matching pursuit(OMP)al⁃gorithm,the model identifies the most significant expansion bases,effectively mitigating the"curse of dimensionality"and pre⁃venting overfitting even with small sample sizes.Additionally,variable transformations are introduced to convert absolute co⁃ordinates into relative distances and angles,significantly enhancing the model's predictive capability.The experimental re⁃sults 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 determi⁃nation coefficient R2>0.9.Critically,the prediction efficiency reaches the millisecond level,representing a transformative in⁃crease in speed compared to traditional full-wave electromagnetic simulations.Furthermore,sensitivity analysis using So⁃bol's method reveals that the relative distance between the wireless device and the human body is the dominant factor influ⁃encing the SAR peak.In conclusion,the proposed rapid SAR estimation method establishes a closed-loop link between"Elec⁃tromagnetic Environment","Human Radiation Dose","Prediction Model",and"Sensitivity Analysis".This work lays the the⁃oretical 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.