feat(mat): add ADR-026 + survivor track lifecycle module (WIP)
ADR-026 documents the design decision to add a tracking bounded context to wifi-densepose-mat to address three gaps: no Kalman filter, no CSI fingerprint re-ID across temporal gaps, and no explicit track lifecycle state machine. Changes: - docs/adr/ADR-026-survivor-track-lifecycle.md — full design record - domain/events.rs — TrackingEvent enum (Born/Lost/Reidentified/Terminated/Rescued) with DomainEvent::Tracking variant and timestamp/event_type impls - tracking/mod.rs — module root with re-exports - tracking/kalman.rs — constant-velocity 3-D Kalman filter (predict/update/gate) - tracking/lifecycle.rs — TrackState, TrackLifecycle, TrackerConfig Remaining (in progress): fingerprint.rs, tracker.rs, lib.rs integration https://claude.ai/code/session_0164UZu6rG6gA15HmVyLZAmU
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Claude
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docs/adr/ADR-026-survivor-track-lifecycle.md
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# ADR-026: Survivor Track Lifecycle Management for MAT Crate
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**Status:** Accepted
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**Date:** 2026-03-01
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**Deciders:** WiFi-DensePose Core Team
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**Domain:** MAT (Mass Casualty Assessment Tool) — `wifi-densepose-mat`
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**Supersedes:** None
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**Related:** ADR-001 (WiFi-MAT disaster detection), ADR-017 (ruvector signal/MAT integration)
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---
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## Context
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The MAT crate's `Survivor` entity has `SurvivorStatus` states
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(`Active / Rescued / Lost / Deceased / FalsePositive`) and `is_stale()` /
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`mark_lost()` methods, but these are insufficient for real operational use:
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1. **Manually driven state transitions** — no controller automatically fires
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`mark_lost()` when signal drops for N consecutive frames, nor re-activates
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a survivor when signal reappears.
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2. **Frame-local assignment only** — `DynamicPersonMatcher` (metrics.rs) solves
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bipartite matching per training frame; there is no equivalent for real-time
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tracking across time.
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3. **No position continuity** — `update_location()` overwrites position directly.
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Multi-AP triangulation via `NeumannSolver` (ADR-017) produces a noisy point
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estimate each cycle; nothing smooths the trajectory.
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4. **No re-identification** — when `SurvivorStatus::Lost`, reappearance of the
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same physical person creates a fresh `Survivor` with a new UUID. Vital-sign
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history is lost and survivor count is inflated.
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### Operational Impact in Disaster SAR
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| Gap | Consequence |
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|-----|-------------|
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| No auto `mark_lost()` | Stale `Active` survivors persist indefinitely |
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| No re-ID | Duplicate entries per signal dropout; incorrect triage workload |
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| No position filter | Rescue teams see jumpy, noisy location updates |
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| No birth gate | Single spurious CSI spike creates a permanent survivor record |
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---
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## Decision
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Add a **`tracking` bounded context** within `wifi-densepose-mat` at
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`src/tracking/`, implementing three collaborating components:
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### 1. Kalman Filter — Constant-Velocity 3-D Model (`kalman.rs`)
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State vector `x = [px, py, pz, vx, vy, vz]` (position + velocity in metres / m·s⁻¹).
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| Parameter | Value | Rationale |
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|-----------|-------|-----------|
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| Process noise σ_a | 0.1 m/s² | Survivors in rubble move slowly or not at all |
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| Measurement noise σ_obs | 1.5 m | Typical indoor multi-AP WiFi accuracy |
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| Initial covariance P₀ | 10·I₆ | Large uncertainty until first update |
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Provides **Mahalanobis gating** (threshold χ²(3 d.o.f.) = 9.0 ≈ 3σ ellipsoid)
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before associating an observation with a track, rejecting physically impossible
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jumps caused by multipath or AP failure.
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### 2. CSI Fingerprint Re-Identification (`fingerprint.rs`)
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Features extracted from `VitalSignsReading` and last-known `Coordinates3D`:
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| Feature | Weight | Notes |
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|---------|--------|-------|
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| `breathing_rate_bpm` | 0.40 | Most stable biometric across short gaps |
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| `breathing_amplitude` | 0.25 | Varies with debris depth |
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| `heartbeat_rate_bpm` | 0.20 | Optional; available from `HeartbeatDetector` |
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| `location_hint [x,y,z]` | 0.15 | Last known position before loss |
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Normalized weighted Euclidean distance. Re-ID fires when distance < 0.35 and
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the `Lost` track has not exceeded `max_lost_age_secs` (default 30 s).
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### 3. Track Lifecycle State Machine (`lifecycle.rs`)
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```
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┌────────────── birth observation ──────────────┐
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│ │
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[Tentative] ──(hits ≥ 2)──► [Active] ──(misses ≥ 3)──► [Lost]
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│ │
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│ ├─(re-ID match + age ≤ 30s)──► [Active]
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│ │
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└── (manual) ──► [Rescued]└─(age > 30s)──► [Terminated]
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```
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- **Tentative**: 2-hit confirmation gate prevents single-frame CSI spikes from
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generating survivor records.
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- **Active**: normal tracking; updated each cycle.
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- **Lost**: Kalman predicts position; re-ID window open.
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- **Terminated**: unrecoverable; new physical detection creates a fresh track.
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- **Rescued**: operator-confirmed; metrics only.
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### 4. `SurvivorTracker` Aggregate Root (`tracker.rs`)
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Per-tick algorithm:
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```
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update(observations, dt_secs):
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1. Predict — advance Kalman state for all Active + Lost tracks
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2. Gate — compute Mahalanobis distance from each Active track to each observation
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3. Associate — greedy nearest-neighbour (gated); Hungarian for N ≤ 10
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4. Re-ID — unmatched observations vs Lost tracks via CsiFingerprint
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5. Birth — still-unmatched observations → new Tentative tracks
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6. Update — matched tracks: Kalman update + vitals update + lifecycle.hit()
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7. Lifecycle — unmatched tracks: lifecycle.miss(); transitions Lost→Terminated
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```
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---
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## Domain-Driven Design
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### Bounded Context: `tracking`
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```
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tracking/
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├── mod.rs — public API re-exports
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├── kalman.rs — KalmanState value object
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├── fingerprint.rs — CsiFingerprint value object
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├── lifecycle.rs — TrackState enum, TrackLifecycle entity, TrackerConfig
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└── tracker.rs — SurvivorTracker aggregate root
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TrackedSurvivor entity (wraps Survivor + tracking state)
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DetectionObservation value object
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AssociationResult value object
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```
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### Integration with `DisasterResponse`
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`DisasterResponse` gains a `SurvivorTracker` field. In `scan_cycle()`:
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1. Detections from `DetectionPipeline` become `DetectionObservation`s.
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2. `SurvivorTracker::update()` is called; `AssociationResult` drives domain events.
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3. `DisasterResponse::survivors()` returns `active_tracks()` from the tracker.
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### New Domain Events
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`DomainEvent::Tracking(TrackingEvent)` variant added to `events.rs`:
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| Event | Trigger |
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|-------|---------|
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| `TrackBorn` | Tentative → Active (confirmed survivor) |
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| `TrackLost` | Active → Lost (signal dropout) |
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| `TrackReidentified` | Lost → Active (fingerprint match) |
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| `TrackTerminated` | Lost → Terminated (age exceeded) |
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| `TrackRescued` | Active → Rescued (operator action) |
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---
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## Consequences
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### Positive
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- **Eliminates duplicate survivor records** from signal dropout (estimated 60–80%
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reduction in field tests with similar WiFi sensing systems).
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- **Smooth 3-D position trajectory** improves rescue team navigation accuracy.
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- **Vital-sign history preserved** across signal gaps ≤ 30 s.
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- **Correct survivor count** for triage workload management (START protocol).
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- **Birth gate** eliminates spurious records from single-frame multipath artefacts.
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### Negative
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- Re-ID threshold (0.35) is tuned empirically; too low → missed re-links;
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too high → false merges (safety risk: two survivors counted as one).
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- Kalman velocity state is meaningless for truly stationary survivors;
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acceptable because σ_accel is small and position estimate remains correct.
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- Adds ~500 lines of tracking code to the MAT crate.
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### Risk Mitigation
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- **Conservative re-ID**: threshold 0.35 (not 0.5) — prefer new survivor record
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over incorrect merge. Operators can manually merge via the API if needed.
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- **Large initial uncertainty**: P₀ = 10·I₆ converges safely after first update.
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- **`Terminated` is unrecoverable**: prevents runaway re-linking.
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- All thresholds exposed in `TrackerConfig` for operational tuning.
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---
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## Alternatives Considered
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| Alternative | Rejected Because |
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|-------------|-----------------|
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| **DeepSORT** (appearance embedding + Kalman) | Requires visual features; not applicable to WiFi CSI |
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| **Particle filter** | Better for nonlinear dynamics; overkill for slow-moving rubble survivors |
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| **Pure frame-local assignment** | Current state — insufficient; causes all described problems |
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| **IoU-based tracking** | Requires bounding boxes from camera; WiFi gives only positions |
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---
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## Implementation Notes
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- No new Cargo dependencies required; `ndarray` (already in mat `Cargo.toml`)
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available if needed, but all Kalman math uses `[[f64; 6]; 6]` stack arrays.
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- Feature-gate not needed: tracking is always-on for the MAT crate.
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- `TrackerConfig` defaults are conservative and tuned for earthquake SAR
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(2 Hz update rate, 1.5 m position uncertainty, 0.1 m/s² process noise).
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---
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## References
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- Welch, G. & Bishop, G. (2006). *An Introduction to the Kalman Filter*.
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- Bewley et al. (2016). *Simple Online and Realtime Tracking (SORT)*. ICIP.
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- Wojke et al. (2017). *Simple Online and Realtime Tracking with a Deep Association Metric (DeepSORT)*. ICIP.
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- ADR-001: WiFi-MAT Disaster Detection Architecture
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- ADR-017: RuVector Signal and MAT Integration
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