**Status:** Proposed

**Date:** 2026-03-15

**Deciders:** @ruvnet

**Related:** ADR-014 (SOTA signal processing), ADR-021 (vital sign extraction), ADR-029 (RuvSense multistatic), ADR-039 (edge intelligence), ADR-042 (CHCI coherent sensing)

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.

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.

**Live hardware capture (COM4, 2026-03-15)** from a Seeed MR60BHA2 on an ESP32-C6 running ESPHome:

Fusing WiFi CSI with mmWave radar creates a sensor system that is greater than the sum of its parts:

| Capability | WiFi CSI Alone | mmWave Alone | Fused |

|-----------|---------------|-------------|-------|

| Through-wall sensing | Yes (5m+) | No (LoS only, ~3m) | Yes — CSI for room-scale, mmWave for precision |

| Heart rate accuracy | ±5-10 BPM | ±1-2 BPM | ±1-2 BPM (mmWave primary, CSI cross-validates) |

| Breathing accuracy | ±2-3 BPM | ±0.5 BPM | ±0.5 BPM |

| Presence detection | Good (adaptive threshold) | Excellent (range-gated) | Excellent + through-wall |

| Multi-person | Via subcarrier clustering | Via range-Doppler bins | Combined spatial + RF resolution |

| Fall detection | Phase acceleration | Range/velocity + micro-Doppler | Dual-confirm reduces false positives to near-zero |

| Pose estimation | Via trained model | Not available | CSI provides pose; mmWave provides ground-truth vitals for training |

| Coverage | Whole room (passive) | ~120° cone, 3m range | Full room + precision zone |

| Cost per node | ~$9 (ESP32-S3) | ~$15 (ESP32-C6 + MR60BHA2) | ~$24 combined |

The RuVector v2.0.4 stack (already integrated per ADR-016) provides the signal processing backbone:

| RuVector Component | Role in mmWave Fusion |

|-------------------|----------------------|

| `ruvector-attention` (`bvp.rs`) | Blood Volume Pulse estimation — mmWave heart rate can calibrate the WiFi CSI BVP phase extraction |

| `ruvector-temporal-tensor` (`breathing.rs`) | Breathing rate estimation — mmWave provides ground-truth for adaptive filter tuning |

| `ruvector-solver` (`triangulation.rs`) | Multilateration — mmWave range-gated distance + CSI amplitude = 3D position |

| `ruvector-attn-mincut` (`spectrogram.rs`) | Time-frequency decomposition — mmWave Doppler complements CSI phase spectrogram |

| `ruvector-mincut` (`metrics.rs`, DynamicPersonMatcher) | Multi-person association — mmWave target IDs help disambiguate CSI subcarrier clusters |

The RuvSense multistatic sensing pipeline (ADR-029) gains new capabilities:

| RuvSense Module | mmWave Integration |

|----------------|-------------------|

| `pose_tracker.rs` (AETHER re-ID) | mmWave distance + velocity as additional re-ID features for Kalman tracker |

| `longitudinal.rs` (Welford stats) | mmWave vitals as reference signal for CSI drift detection |

| `intention.rs` (pre-movement) | mmWave micro-Doppler detects pre-movement 100-200ms earlier than CSI |

| `adversarial.rs` (consistency check) | mmWave provides independent signal to detect CSI spoofing/anomalies |

| `coherence_gate.rs` | mmWave presence as additional gate input — if mmWave says "no person", CSI coherence gate rejects |

The viewpoint fusion pipeline (`ruvector/src/viewpoint/`) extends naturally:

| Viewpoint Module | mmWave Extension |

|-----------------|-----------------|

| `attention.rs` (CrossViewpointAttention) | mmWave range becomes a new "viewpoint" in the attention mechanism |

| `geometry.rs` (GeometricDiversityIndex) | mmWave cone geometry contributes to Fisher Information / Cramer-Rao bounds |

| `coherence.rs` (phase phasor) | mmWave phase coherence as validation for WiFi phasor coherence |

| `fusion.rs` (MultistaticArray) | mmWave node becomes a member of the multistatic array with its own domain events |

Add 60 GHz mmWave radar sensor support to the RuView firmware and sensing pipeline with auto-detection and device-specific capabilities.

**Mode 1: Standalone CSI (existing)** — ESP32-S3 only, WiFi CSI sensing.

**Mode 2: Standalone mmWave** — ESP32-C6 + MR60BHA2, precise vitals in a single room.

**Mode 3: Fused (recommended)** — ESP32-S3 + mmWave module on UART, or two separate nodes with server-side fusion.

The firmware will auto-detect connected mmWave modules at boot:

1. **UART probe** — On configured UART pins, send the MR60BHA2 identification command (`0x01 0x01 0x00 0x01 ...`) and check for valid response header

2. **Protocol detection** — Identify the sensor family:

- Seeed MR60BHA2 (breathing + heart rate)

- Seeed MR60FDA1 (fall detection)

- Seeed MR24HPC1 (presence + light sleep/deep sleep)

- HLK-LD2410 (presence + distance)

- HLK-LD2450 (multi-target tracking)

3. **Capability registration** — Register detected sensor capabilities in the edge config:

typedef struct {

uint8_t mmwave_detected; /** 1 if mmWave module found on UART */

uint8_t mmwave_type; /** Sensor family (MR60BHA2, MR60FDA1, etc.) */

uint8_t mmwave_has_hr; /** Heart rate capability */

uint8_t mmwave_has_br; /** Breathing rate capability */

uint8_t mmwave_has_fall; /** Fall detection capability */

uint8_t mmwave_has_presence; /** Presence detection capability */

uint8_t mmwave_has_distance; /** Range measurement capability */

uint8_t mmwave_has_tracking; /** Multi-target tracking capability */

float mmwave_hr_bpm; /** Latest heart rate from mmWave */

float mmwave_br_bpm; /** Latest breathing rate from mmWave */

float mmwave_distance_cm; /** Distance to nearest target */

uint8_t mmwave_target_count; /** Number of detected targets */

bool mmwave_person_present;/** mmWave presence state */

} mmwave_state_t;

| Sensor | Frequency | Capabilities | UART Protocol | Cost |

|--------|-----------|-------------|---------------|------|

| **Seeed MR60BHA2** | 60 GHz | HR, BR, presence, illuminance | Seeed proprietary frames | ~$15 |

| **Seeed MR60FDA1** | 60 GHz | Fall detection, presence | Seeed proprietary frames | ~$15 |

| **Seeed MR24HPC1** | 24 GHz | Presence, sleep stage, distance | Seeed proprietary frames | ~$10 |

| **HLK-LD2410** | 24 GHz | Presence, distance (motion + static) | HLK binary protocol | ~$3 |

| **HLK-LD2450** | 24 GHz | Multi-target tracking (x,y,speed) | HLK binary protocol | ~$5 |

**1. Vital Sign Fusion (Kalman filter)**

**2. Fall Detection (dual-confirm)**

**3. Presence Validation**

**4. Training Calibration**

Extend the existing 32-byte vitals packet (magic `0xC5110002`) with a new 48-byte fused packet:

typedef struct __attribute__((packed)) {

/* Existing 32-byte vitals fields */

uint32_t magic; /* 0xC5110004 (fused vitals) */

uint8_t node_id;

uint8_t flags; /* Bit0=presence, Bit1=fall, Bit2=motion, Bit3=mmwave_present */

uint16_t breathing_rate; /* Fused BPM * 100 */

uint32_t heartrate; /* Fused BPM * 10000 */

int8_t rssi;

uint8_t n_persons;

uint8_t mmwave_type; /* Sensor type enum */

uint8_t fusion_confidence;/* 0-100 fusion quality score */

float motion_energy;

float presence_score;

uint32_t timestamp_ms;

/* New mmWave fields (16 bytes) */

float mmwave_hr_bpm; /* Raw mmWave heart rate */

float mmwave_br_bpm; /* Raw mmWave breathing rate */

float mmwave_distance; /* Distance to nearest target (cm) */

uint8_t mmwave_targets; /* Target count */

uint8_t mmwave_confidence;/* mmWave signal quality 0-100 */

uint16_t reserved;

} edge_fused_vitals_pkt_t;

_Static_assert(sizeof(edge_fused_vitals_pkt_t) == 48, "fused vitals must be 48 bytes");

| Phase | Scope | Effort |

|-------|-------|--------|

| **Phase 1** | UART driver + MR60BHA2 parser + auto-detection | 2 weeks |

| **Phase 2** | Fused vitals packet + Kalman vital sign fusion | 1 week |

| **Phase 3** | Dual-confirm fall detection + presence voting | 1 week |

| **Phase 4** | HLK-LD2410/LD2450 support + multi-target fusion | 2 weeks |

| **Phase 5** | RuVector calibration pipeline (mmWave as ground truth) | 3 weeks |

| **Phase 6** | Server-side fusion for separate CSI + mmWave nodes | 2 weeks |

- Near-zero false positive fall detection (dual-confirm)

- Clinical-grade vital signs when mmWave is present, with CSI as fallback

- Self-calibrating CSI pipeline using mmWave ground truth

- Backward compatible — existing CSI-only nodes work unchanged

- Low incremental cost (~$3-15 per mmWave module)

- Auto-detection means zero configuration for supported sensors

- RuVector attention/solver/temporal-tensor modules gain a high-quality reference signal

- Added firmware complexity (~2-3 KB RAM for mmWave state + UART buffer)

- mmWave modules require line-of-sight (complementary to CSI, not replacement)

- Multiple UART protocols to maintain (Seeed, HLK families)

- 48-byte fused packet requires server parser update

- ESP32-C6 cannot run the full CSI pipeline (single-core RISC-V) but can serve as a dedicated mmWave bridge node

- mmWave modules add ~15 mA power draw per node