RFRF Capture Technology Basics: How It Works
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This article explains the basics of RF capture technology, including its features, and how it works. We are familiar with various image processing techniques for humans, such as X-ray, visible light, terahertz, and millimeter-wave imaging.
RF capture technology operates at much lower power levels compared to these established techniques. Moreover, it utilizes a lower RF carrier frequency, typically between 5.46 GHz and 7.24 GHz. Sensors are a core component of the RF capture system.
The following table outlines key features of RF capture technology:
| Specifications | RF Capture technology |
|---|---|
| Transmit Power | 1/1000 of WiFi signal power |
| Frequency Range | Between 5.46GHz and 7.24GHz |
| Method of detection | Reflection from some of the parts of human body |
| Coverage Range | Less than 100 meters |
| Accuracy | Varies based on identification type (body parts, movement, number of people) and distance from the system. |
| Applications | To determine person behind walls, determine handwriting of person from behind wall, movement of person etc. |
How RF Capture Works
Here’s a breakdown of the steps involved in how RF capture works:
- The system, positioned behind a wall, transmits an RF signal that penetrates the wall but reflects off different parts of the human body.
- These multiple reflections are captured at various points in time.
- Based on these recorded snapshots and using a reconstruction algorithm, the RF capture system develops a human sketch, as illustrated in the figure.
The following capabilities are inherent to RF capture technology:
- Limb Position Estimation: RF capture technology estimates the positions of different limbs of the human body, such as the head, chest, arms, and feet.
- Posture Estimation: The system estimates different postures of the human being.
- Snapshot Generation: The RF capture system generates distinct snapshots for different types of individuals.
- Movement Detection: It can also determine the movement of human beings.
REFERENCE: This article is based on research conducted at the Massachusetts Institute of Technology. For more detailed information, please read their published paper.
