docs: ADR-063 mmWave sensor fusion with WiFi CSI
60 GHz mmWave radar (Seeed MR60BHA2, HLK-LD2410/LD2450) fusion with WiFi CSI for dual-confirm fall detection, clinical-grade vitals, and self-calibrating CSI pipeline. Covers auto-detection, 6 supported sensors, Kalman fusion, extended 48-byte vitals packet, RuVector/RuvSense integration points, and 6-phase implementation plan. Based on live hardware capture from ESP32-C6 + MR60BHA2 on COM4. Co-Authored-By: claude-flow <ruv@ruv.net>
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# ADR-063: 60 GHz mmWave Sensor Fusion with WiFi CSI
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**Status:** Proposed
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**Date:** 2026-03-15
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**Deciders:** @ruvnet
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**Related:** ADR-014 (SOTA signal processing), ADR-021 (vital sign extraction), ADR-029 (RuvSense multistatic), ADR-039 (edge intelligence), ADR-042 (CHCI coherent sensing)
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## Context
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RuView currently senses the environment using WiFi CSI — a passive technique that analyzes how WiFi signals are disturbed by human presence and movement. While this works through walls and requires no line of sight, CSI-derived vital signs (breathing rate, heart rate) are inherently noisy because they rely on phase extraction from multipath-rich WiFi channels.
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A complementary sensing modality exists: **60 GHz mmWave radar** modules (e.g., Seeed MR60BHA2) that use active FMCW radar at 60 GHz to measure breathing and heart rate with clinical-grade accuracy. These modules are inexpensive (~$15), run on ESP32-C6/C3, and output structured vital signs over UART.
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**Live hardware capture (COM4, 2026-03-15)** from a Seeed MR60BHA2 on an ESP32-C6 running ESPHome:
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```
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[D][sensor:093]: 'Real-time respiratory rate': Sending state 22.00000
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[D][sensor:093]: 'Real-time heart rate': Sending state 92.00000 bpm
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[D][sensor:093]: 'Distance to detection object': Sending state 0.00000 cm
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[D][sensor:093]: 'Target Number': Sending state 0.00000
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[D][binary_sensor:036]: 'Person Information': Sending state OFF
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[D][sensor:093]: 'Seeed MR60BHA2 Illuminance': Sending state 0.67913 lx
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```
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### The Opportunity
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Fusing WiFi CSI with mmWave radar creates a sensor system that is greater than the sum of its parts:
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| Capability | WiFi CSI Alone | mmWave Alone | Fused |
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|-----------|---------------|-------------|-------|
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| Through-wall sensing | Yes (5m+) | No (LoS only, ~3m) | Yes — CSI for room-scale, mmWave for precision |
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| Heart rate accuracy | ±5-10 BPM | ±1-2 BPM | ±1-2 BPM (mmWave primary, CSI cross-validates) |
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| Breathing accuracy | ±2-3 BPM | ±0.5 BPM | ±0.5 BPM |
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| Presence detection | Good (adaptive threshold) | Excellent (range-gated) | Excellent + through-wall |
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| Multi-person | Via subcarrier clustering | Via range-Doppler bins | Combined spatial + RF resolution |
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| Fall detection | Phase acceleration | Range/velocity + micro-Doppler | Dual-confirm reduces false positives to near-zero |
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| Pose estimation | Via trained model | Not available | CSI provides pose; mmWave provides ground-truth vitals for training |
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| Coverage | Whole room (passive) | ~120° cone, 3m range | Full room + precision zone |
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| Cost per node | ~$9 (ESP32-S3) | ~$15 (ESP32-C6 + MR60BHA2) | ~$24 combined |
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### RuVector Integration Points
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The RuVector v2.0.4 stack (already integrated per ADR-016) provides the signal processing backbone:
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| RuVector Component | Role in mmWave Fusion |
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|-------------------|----------------------|
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| `ruvector-attention` (`bvp.rs`) | Blood Volume Pulse estimation — mmWave heart rate can calibrate the WiFi CSI BVP phase extraction |
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| `ruvector-temporal-tensor` (`breathing.rs`) | Breathing rate estimation — mmWave provides ground-truth for adaptive filter tuning |
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| `ruvector-solver` (`triangulation.rs`) | Multilateration — mmWave range-gated distance + CSI amplitude = 3D position |
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| `ruvector-attn-mincut` (`spectrogram.rs`) | Time-frequency decomposition — mmWave Doppler complements CSI phase spectrogram |
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| `ruvector-mincut` (`metrics.rs`, DynamicPersonMatcher) | Multi-person association — mmWave target IDs help disambiguate CSI subcarrier clusters |
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### RuvSense Integration Points
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The RuvSense multistatic sensing pipeline (ADR-029) gains new capabilities:
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| RuvSense Module | mmWave Integration |
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|----------------|-------------------|
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| `pose_tracker.rs` (AETHER re-ID) | mmWave distance + velocity as additional re-ID features for Kalman tracker |
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| `longitudinal.rs` (Welford stats) | mmWave vitals as reference signal for CSI drift detection |
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| `intention.rs` (pre-movement) | mmWave micro-Doppler detects pre-movement 100-200ms earlier than CSI |
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| `adversarial.rs` (consistency check) | mmWave provides independent signal to detect CSI spoofing/anomalies |
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| `coherence_gate.rs` | mmWave presence as additional gate input — if mmWave says "no person", CSI coherence gate rejects |
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### Cross-Viewpoint Fusion Integration
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The viewpoint fusion pipeline (`ruvector/src/viewpoint/`) extends naturally:
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| Viewpoint Module | mmWave Extension |
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|-----------------|-----------------|
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| `attention.rs` (CrossViewpointAttention) | mmWave range becomes a new "viewpoint" in the attention mechanism |
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| `geometry.rs` (GeometricDiversityIndex) | mmWave cone geometry contributes to Fisher Information / Cramer-Rao bounds |
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| `coherence.rs` (phase phasor) | mmWave phase coherence as validation for WiFi phasor coherence |
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| `fusion.rs` (MultistaticArray) | mmWave node becomes a member of the multistatic array with its own domain events |
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## Decision
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Add 60 GHz mmWave radar sensor support to the RuView firmware and sensing pipeline with auto-detection and device-specific capabilities.
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### Architecture
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```
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┌─────────────────────────────────────────────────────────┐
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│ Sensing Node │
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│ │
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│ ┌──────────────┐ ┌──────────────┐ ┌────────────┐ │
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│ │ ESP32-S3 │ │ ESP32-C6 │ │ Combined │ │
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│ │ WiFi CSI │ │ + MR60BHA2 │ │ S3 + UART │ │
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│ │ (COM7) │ │ 60GHz mmWave │ │ mmWave │ │
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│ │ │ │ (COM4) │ │ │ │
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│ │ Passive │ │ Active radar │ │ Both modes │ │
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│ │ Through-wall │ │ LoS, precise │ │ │ │
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│ └──────┬───────┘ └──────┬───────┘ └─────┬──────┘ │
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│ │ │ │ │
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│ └────────┬───────────┘ │ │
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│ ▼ │ │
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│ ┌────────────────┐ │ │
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│ │ Fusion Engine │◄──────────────────────┘ │
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│ │ │ │
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│ │ • Kalman fuse │ Vitals packet (extended): │
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│ │ • Cross-validate│ magic 0xC5110004 │
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│ │ • Ground-truth │ + mmwave_hr, mmwave_br │
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│ │ calibration │ + mmwave_distance │
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│ │ • Fall confirm │ + mmwave_target_count │
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│ └────────────────┘ + confidence scores │
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└─────────────────────────────────────────────────────────┘
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```
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### Three Deployment Modes
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**Mode 1: Standalone CSI (existing)** — ESP32-S3 only, WiFi CSI sensing.
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**Mode 2: Standalone mmWave** — ESP32-C6 + MR60BHA2, precise vitals in a single room.
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**Mode 3: Fused (recommended)** — ESP32-S3 + mmWave module on UART, or two separate nodes with server-side fusion.
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### Auto-Detection Protocol
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The firmware will auto-detect connected mmWave modules at boot:
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1. **UART probe** — On configured UART pins, send the MR60BHA2 identification command (`0x01 0x01 0x00 0x01 ...`) and check for valid response header
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2. **Protocol detection** — Identify the sensor family:
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- Seeed MR60BHA2 (breathing + heart rate)
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- Seeed MR60FDA1 (fall detection)
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- Seeed MR24HPC1 (presence + light sleep/deep sleep)
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- HLK-LD2410 (presence + distance)
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- HLK-LD2450 (multi-target tracking)
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3. **Capability registration** — Register detected sensor capabilities in the edge config:
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```c
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typedef struct {
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uint8_t mmwave_detected; /** 1 if mmWave module found on UART */
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uint8_t mmwave_type; /** Sensor family (MR60BHA2, MR60FDA1, etc.) */
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uint8_t mmwave_has_hr; /** Heart rate capability */
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uint8_t mmwave_has_br; /** Breathing rate capability */
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uint8_t mmwave_has_fall; /** Fall detection capability */
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uint8_t mmwave_has_presence; /** Presence detection capability */
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uint8_t mmwave_has_distance; /** Range measurement capability */
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uint8_t mmwave_has_tracking; /** Multi-target tracking capability */
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float mmwave_hr_bpm; /** Latest heart rate from mmWave */
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float mmwave_br_bpm; /** Latest breathing rate from mmWave */
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float mmwave_distance_cm; /** Distance to nearest target */
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uint8_t mmwave_target_count; /** Number of detected targets */
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bool mmwave_person_present;/** mmWave presence state */
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} mmwave_state_t;
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```
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### Supported Sensors
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| Sensor | Frequency | Capabilities | UART Protocol | Cost |
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|--------|-----------|-------------|---------------|------|
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| **Seeed MR60BHA2** | 60 GHz | HR, BR, presence, illuminance | Seeed proprietary frames | ~$15 |
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| **Seeed MR60FDA1** | 60 GHz | Fall detection, presence | Seeed proprietary frames | ~$15 |
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| **Seeed MR24HPC1** | 24 GHz | Presence, sleep stage, distance | Seeed proprietary frames | ~$10 |
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| **HLK-LD2410** | 24 GHz | Presence, distance (motion + static) | HLK binary protocol | ~$3 |
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| **HLK-LD2450** | 24 GHz | Multi-target tracking (x,y,speed) | HLK binary protocol | ~$5 |
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### Fusion Algorithms
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**1. Vital Sign Fusion (Kalman filter)**
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```
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mmWave HR (high confidence, 1 Hz) ─┐
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├─► Kalman fuse → fused HR ± confidence
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CSI-derived HR (lower confidence) ─┘
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```
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**2. Fall Detection (dual-confirm)**
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```
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CSI phase accel > thresh ──────┐
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├─► AND gate → confirmed fall (near-zero false positives)
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mmWave range-velocity pattern ─┘
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```
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**3. Presence Validation**
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```
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CSI adaptive threshold ────┐
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├─► Weighted vote → robust presence
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mmWave target count > 0 ──┘
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```
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**4. Training Calibration**
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```
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mmWave ground-truth vitals → train CSI BVP extraction model
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mmWave distance → calibrate CSI triangulation
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mmWave micro-Doppler → label CSI activity patterns
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```
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### Vitals Packet Extension
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Extend the existing 32-byte vitals packet (magic `0xC5110002`) with a new 48-byte fused packet:
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```c
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typedef struct __attribute__((packed)) {
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/* Existing 32-byte vitals fields */
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uint32_t magic; /* 0xC5110004 (fused vitals) */
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uint8_t node_id;
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uint8_t flags; /* Bit0=presence, Bit1=fall, Bit2=motion, Bit3=mmwave_present */
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uint16_t breathing_rate; /* Fused BPM * 100 */
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uint32_t heartrate; /* Fused BPM * 10000 */
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int8_t rssi;
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uint8_t n_persons;
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uint8_t mmwave_type; /* Sensor type enum */
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uint8_t fusion_confidence;/* 0-100 fusion quality score */
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float motion_energy;
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float presence_score;
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uint32_t timestamp_ms;
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/* New mmWave fields (16 bytes) */
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float mmwave_hr_bpm; /* Raw mmWave heart rate */
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float mmwave_br_bpm; /* Raw mmWave breathing rate */
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float mmwave_distance; /* Distance to nearest target (cm) */
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uint8_t mmwave_targets; /* Target count */
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uint8_t mmwave_confidence;/* mmWave signal quality 0-100 */
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uint16_t reserved;
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} edge_fused_vitals_pkt_t;
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_Static_assert(sizeof(edge_fused_vitals_pkt_t) == 48, "fused vitals must be 48 bytes");
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```
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### NVS Configuration
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New provisioning parameters:
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```bash
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python provision.py --port COM7 \
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--mmwave-uart-tx 17 --mmwave-uart-rx 18 \ # UART pins for mmWave module
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--mmwave-type auto \ # auto-detect, or: mr60bha2, ld2410, etc.
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--fusion-mode kalman \ # kalman, vote, mmwave-primary, csi-primary
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--fall-dual-confirm true # require both CSI + mmWave for fall alert
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```
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### Implementation Phases
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| Phase | Scope | Effort |
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|-------|-------|--------|
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| **Phase 1** | UART driver + MR60BHA2 parser + auto-detection | 2 weeks |
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| **Phase 2** | Fused vitals packet + Kalman vital sign fusion | 1 week |
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| **Phase 3** | Dual-confirm fall detection + presence voting | 1 week |
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| **Phase 4** | HLK-LD2410/LD2450 support + multi-target fusion | 2 weeks |
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| **Phase 5** | RuVector calibration pipeline (mmWave as ground truth) | 3 weeks |
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| **Phase 6** | Server-side fusion for separate CSI + mmWave nodes | 2 weeks |
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## Consequences
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### Positive
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- Near-zero false positive fall detection (dual-confirm)
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- Clinical-grade vital signs when mmWave is present, with CSI as fallback
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- Self-calibrating CSI pipeline using mmWave ground truth
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- Backward compatible — existing CSI-only nodes work unchanged
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- Low incremental cost (~$3-15 per mmWave module)
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- Auto-detection means zero configuration for supported sensors
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- RuVector attention/solver/temporal-tensor modules gain a high-quality reference signal
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### Negative
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- Added firmware complexity (~2-3 KB RAM for mmWave state + UART buffer)
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- mmWave modules require line-of-sight (complementary to CSI, not replacement)
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- Multiple UART protocols to maintain (Seeed, HLK families)
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- 48-byte fused packet requires server parser update
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### Neutral
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- ESP32-C6 cannot run the full CSI pipeline (single-core RISC-V) but can serve as a dedicated mmWave bridge node
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- mmWave modules add ~15 mA power draw per node
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