RuView Advanced Sensing

The deep end: multistatic mesh, tomography, persistent field models, and the security model that protects them. Most of this lives in wifi-densepose-signal/src/ruvsense/ (14 modules) and wifi-densepose-ruvector/src/viewpoint/ (5 modules).

RuvSense multistatic mode (ADR-029)

Treat every WiFi link in range — including neighbours' APs — as a bistatic radar pair, then fuse them.

Module (signal/src/ruvsense/)	Purpose
multiband.rs	Multi-band CSI frame fusion, cross-channel coherence
phase_align.rs	Iterative LO phase-offset estimation, circular mean
multistatic.rs	Attention-weighted fusion, geometric diversity
coherence.rs / coherence_gate.rs	Z-score coherence scoring; Accept / PredictOnly / Reject / Recalibrate gate decisions
pose_tracker.rs	17-keypoint Kalman tracker with AETHER re-ID embeddings
field_model.rs	SVD room eigenstructure, perturbation extraction
tomography.rs	RF tomography, ISTA L1 solver, voxel grid
longitudinal.rs	Welford stats, biomechanics drift detection
intention.rs	Pre-movement lead signals (200–500 ms ahead)
cross_room.rs	Environment fingerprinting, transition graph
gesture.rs	DTW template-matching gesture classifier
adversarial.rs	Physically-impossible-signal detection, multi-link consistency

Cross-viewpoint fusion (ADR-016 viewpoint module)

Combine 2+ nodes geometrically — more nodes, more independent looks, tighter localization.

Module (ruvector/src/viewpoint/)	Purpose
attention.rs	CrossViewpointAttention, GeometricBias, softmax with G_bias
geometry.rs	GeometricDiversityIndex, Cramér–Rao bounds, Fisher Information
coherence.rs	Phase-phasor coherence, hysteresis gate
fusion.rs	MultistaticArray aggregate root, domain events

Host-side helpers to explore the geometry before deploying: node scripts/mesh-graph-transformer.js, node scripts/passive-radar.js, node scripts/deep-scan.js.

Persistent field model (ADR-030)

field_model.rs builds an SVD eigenstructure of the room and stores it (RVF, ideally on a Cognitum Seed). New CSI frames are projected against it; the residual is the perturbation. Lets you ask "what's different from the empty-room baseline?" and survive restarts.

RF tomography

tomography.rs reconstructs a voxel occupancy grid from the multistatic link set via an ISTA L1 solver (sparse — most voxels are empty). Use with cross-viewpoint geometry for through-wall volumetric imaging. RuVector solver crates back the sparse interpolation (114→56 subcarriers).

Sensing-first RF mode & adaptive mesh kernel

• ADR-031 (RuView sensing-first RF mode), ADR-081 (adaptive CSI mesh firmware kernel), ADR-083 (per-cluster π compute hop), ADR-095/096 (on-ESP32 temporal modeling with sparse GQA attention — runs the temporal head on-device).

Security (ADR-032 — multistatic mesh hardening)

Using neighbours' APs as illuminators and pooling links across a mesh expands the attack surface. Mitigations:

• adversarial.rs rejects physically impossible signals and cross-checks multi-link consistency.
• coherence_gate.rs quarantines low-coherence / suspicious links (Reject / Recalibrate).
• Ed25519 witness chain (ADR-028) attests every measurement.
• Run a security review when touching anything on the hardware/network boundary (see ruview-verify and docs/security-audit-wasm-edge-vendor.md).

Validate advanced changes

cd v2 && cargo test --workspace --no-default-features      # incl. ruvsense + viewpoint tests
cargo test -p wifi-densepose-signal --no-default-features
cargo test -p wifi-densepose-ruvector --no-default-features
cd .. && python archive/v1/data/proof/verify.py

Reference

• ADRs: 014 (SOTA signal processing), 029 (multistatic mode), 030 (persistent field model), 031 (sensing-first RF), 032 (mesh security hardening), 081/083/095/096
• v2/crates/wifi-densepose-signal/src/ruvsense/ · v2/crates/wifi-densepose-ruvector/src/viewpoint/
• docs/research/, docs/security-audit-wasm-edge-vendor.md