Wi-Fi Passive Radar — Through-Wall Detection

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The Insight

Wi-Fi signals penetrate walls and reflect off human bodies, creating detectable Doppler shifts and signal disruptions. By processing these reflections from coherent multi-channel receivers, we can detect and localize human presence through walls without active transmission.

Quick Facts

What This Is

A passive radar system that exploits ambient Wi-Fi signals (2.4 GHz / 5 GHz) as illuminators of opportunity for through-wall human detection and localization. The system uses coherent multi-channel RF receivers to process reflected Wi-Fi signals, extracting micro-Doppler signatures and bistatic range information to detect and track human movement.

Core Principles

Wi-Fi as Illumination Source:

• Ubiquitous Coverage: Wi-Fi access points provide dense, continuous illumination in urban/indoor environments
• Wall Penetration: 2.4 GHz signals penetrate common building materials (drywall, wood, brick)
• Reflection Characteristics: Human bodies create significant radar cross-section at Wi-Fi frequencies
• Micro-Doppler Signatures: Breathing, walking, and limb motion create characteristic Doppler patterns

Bistatic Geometry:

• Wi-Fi AP as Transmitter: Existing access points serve as non-cooperative illuminators
• Target Reflection: Human bodies reflect Wi-Fi signals toward receiver array
• Coherent Processing: Multiple receiver channels enable angle-of-arrival estimation and beamforming
• Range-Doppler Mapping: Cross-correlation extracts bistatic range; FFT reveals Doppler shifts from motion

Signal Processing Challenges:

• Direct Signal Cancellation: Remove strong direct path from AP to receiver (adaptive filtering)
• Multipath Suppression: Indoor environments create complex multipath reflections
• Clutter Rejection: Static objects (furniture, walls) must be filtered from moving targets
• Low SNR Operation: Human reflections are weak compared to direct signal and clutter

Detection Capabilities:

• Presence Detection: Identify human presence behind walls
• Motion Classification: Distinguish walking, standing, breathing based on micro-Doppler
• Localization: Estimate position using angle-of-arrival from coherent array
• Tracking: Follow movement over time

Applications

• Emergency Response: Locate people in burning buildings or disaster zones
• Security: Perimeter monitoring and intrusion detection
• Smart Home: Occupancy sensing for automation
• Healthcare: Non-contact breathing/heartbeat monitoring

Technical Approach

The system processes coherent multi-channel Wi-Fi signals using:

1. Reference Signal Extraction: Capture direct Wi-Fi signal from AP
2. Surveillance Channel Processing: Receive reflected signals from multiple antennas
3. Adaptive Interference Cancellation: Remove direct signal and static multipath
4. Beamforming: Spatial filtering to enhance target signals
5. Range-Doppler Processing: Extract target range and velocity
6. Micro-Doppler Analysis: Classify human activity patterns

7. Tracking: Maintain target tracks over time