Approximate Analytical Approach for Fast Prediction of Microwave Sensor Response: Numerical Analysis and Results.

Area of Science:

• Electromagnetics
• Biomedical Engineering
• Sensor Technology

Background:

• Microwave sensors require accurate prediction of electromagnetic interactions with biological tissues for medical applications.
• Full-wave simulations are accurate but computationally expensive for iterative sensor optimization.
• Existing analytical models are often complex and not practical for sensor design.

Purpose of the Study:

• To develop a computationally efficient approximate analytical model for standard-aperture microwave sensors.
• To predict the sensor response (reflection coefficient) when placed above a layered biological medium.
• To provide a practical tool for managing microwave sensor design in medical applications.

Main Methods:

• Developed an approximate analytical model based on the dominant mode assumption for standard-aperture sensors.
• Validated the model by comparing its predictions with full-wave simulations.
• Focused on the 2-3 GHz frequency range relevant for medical applications.

Main Results:

• The approximate analytical model shows strong agreement with full-wave simulations.
• The model effectively predicts the reflection coefficient for sensor-tissue interactions.
• Demonstrated the model's validity as a first-order approximation.

Conclusions:

• The proposed approximate analytical model is a reliable and computationally efficient tool.
• It significantly aids in the design and management of microwave sensors for medical applications.
• Facilitates accurate prediction of electromagnetic interactions between sensors and biological tissues.