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One shared representation instead of another isolated RF classifier: new v2 leaf crate ruview-unified implementing all five ADR-273 pillars, plus six ADRs with measured, grade-labeled results. - Canonical RfTensor + fail-closed hardware adapter registry (802.11 CSI via wifi-densepose-core::CsiFrame, FMCW radar cubes, UWB CIR, 5G SRS); shared layout/gain/phase normalization proven by tests (ADR-274). - Universal RF foundation encoder: CFO-aligned, median-scaled tokenizer; masked-reconstruction pretraining with hand-derived backprop verified against central finite differences (max rel err 1.31e-5 over all 12 parameter groups); fusion contract z = Enc ⊙ σ(AgeEnc) + GeomEnc; task adapters under the 1% budget (129/268/387/2 params vs 40,856 backbone), enforced by test. - RF-aware Gaussian spatial memory: anisotropic primitives with per-band reflectivity, confidence-weighted fusion, decay, spatial-hash/semantic queries, closed-form Beer-Lambert channel gain (exact Friis on empty map), inverse gain updates (unseen 6.1 dB wall learned to <0.5 dB in 20 observations), task-gated scene graph (ADR-275). - Physics-guided synthetic RF worlds: image-method multipath (order ≤2), complex-permittivity Fresnel materials, emergent Doppler proven against the analytic phase rate, seeded ChaCha20 randomization of physics and hardware nuisances; byte-deterministic per seed (ADR-276). - Edge sensing control plane: 802.11bf/ETSI-ISAC-aligned purposes/zones, fail-closed authorization, double-gated identity, retention bounds; BoundedEvent-only trust boundary makes raw RF export unrepresentable (ADR-277). Radar inverse rendering stays a gated research program (ADR-278, no code by design). Anti-leakage acceptance pipeline (strict splits by room/day/person/ chipset/firmware/layout with independent disjointness verification): presence F1 1.00 on held-out rooms and held-out chipset, degradation 0.0, ECE 0.012, p95 latency 2.0 ms debug / 105 µs release — ALL SYNTHETIC until P2 real-data validation. Benchmarks + optimization pass: channel_gain 139→27 µs (O(1) in map size via segment-corridor AABB sweep), observe_link 305→74 µs, DFT twiddle plan 4.9x; hash/linear crossover (~4k Gaussians) reported honestly. Tests: ruview-unified 66 unit + 3 acceptance, 0 failed; workspace 3,771 passed 0 failed (--exclude wifi-densepose-desktop: GTK headers unavailable in this container). Python proof: VERDICT PASS. Also gitignore sensing-server test-run artifacts (incl. generated session-secret). Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01Q1R5zhz6sSfXGRXpgBwpFX
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ADR-278: Radar inverse rendering + differentiable RF SLAM — a gated research program, not a dependency
| Field | Value |
|---|---|
| Status | Proposed — research program (deliberately no code in P1) |
| Date | 2026-07-26 |
| Parent | ADR-273 (pillar 6, score 3.6 — highest strategic value, highest hardware + reproduction risk) |
| Relates to | ADR-275 (the Gaussian memory these methods would write into), ADR-263/264 (RTL8720F radar platform + wire protocol), ADR-021 (mmWave vitals hardware), ADR-276 (synthetic worlds as the reproduction sandbox) |
0. PROOF discipline
Everything numeric in this ADR is EXTERNAL-UNVERIFIED — reported by fresh papers/preprints that this repo has not reproduced. That is the point of this ADR: to fix the reproduction gates before any of these numbers are allowed to influence the roadmap as if they were ours.
1. Context — what the field reports (July 2026)
| System | Claim (theirs) | Availability | Risk read |
|---|---|---|---|
| RISE | Single static mmWave radar + multipath inversion → joint room layout + furniture; 16 cm scene Chamfer (baseline 40 cm), 58 % furniture IoU | code available | most reproducible; static sensor matches our appliance posture |
| DiffRadar | Radar SLAM + Gaussian fields + differentiable rendering; 0.129 m vs 0.823 m ATE, 94.78 % vs 42.59 % map consistency, 70 fps, 40 MB maps | fresh preprint | treat as reproduction target, not component — numbers are single-team, single-venue |
| GeRaF | Differentiable RF renderer + SDF + reflectivity, near-range reconstruction; ~32 h on one H100 for 50 k iterations | published setup | offline calibration / digital-twin tool only; unsuitable for continuous adaptation |
The strategic pull is real: all three converge on inverse rendering into continuous scene representations — exactly the ADR-275 memory. The risks are equally real: single-source numbers, mmWave hardware variance, and compute profiles (GeRaF) incompatible with edge deployment.
2. Decision
- No production dependency on any of these systems or their claims. ADR-275's gain model + inverse update is the only RF-inverse machinery in the deployment path.
- Reproduction order: RISE → DiffRadar → GeRaF-lite, each on one controlled test site, each gated (§3) before the next starts. RISE first because a static radar matches the RuView appliance posture and its inversion writes naturally into
RfGaussian(occupancy + reflectivity fields already exist for it). - Sandbox-first: before hardware, each method's core inversion is exercised against ADR-276 synthetic worlds extended with a radar-cube output mode (the
FmcwRadarCubeadapter already normalizes such cubes), so failures separate into "our reimplementation" vs "their claim" cleanly. - Integration contract: any reproduced system emits into
GaussianMapvia the existing primitive — no parallel scene store. SLAM trajectories, if any, becomeProvenance-stamped map updates subject to ADR-277 export rules like everything else.
3. Gates (each phase passes all or the program pauses)
| Gate | Threshold | Split discipline |
|---|---|---|
| G1 RISE-repro (synthetic) | layout Chamfer within 2× of paper's on our synthetic rooms | held-out room geometries |
| G2 RISE-repro (one real site) | qualitative layout recovery + quantified Chamfer vs measured floor plan; report our number, whatever it is | site never used in tuning |
| G3 DiffRadar-repro | ATE and map consistency on our trajectory rig; publish the delta vs paper | held-out trajectories |
| G4 Edge viability | inversion or map-update loop ≤ 50 ms p95 on target hardware, or explicit reclassification as offline-calibration tooling (GeRaF's honest category) | — |
A gate failure is a result, recorded in this ADR's log — the program exists to convert EXTERNAL-UNVERIFIED into MEASURED, in either direction.
4. Consequences
- The roadmap cannot silently absorb preprint numbers; anything radar-inverse must pass through §3.
- ADR-275's primitive already reserves the fields (per-band × angle reflectivity, occupancy, motion) these methods need, so a successful reproduction integrates without schema churn.
- Cost of delay is accepted: pillar 6 scored lowest on readiness, and P1–P4 (encoder, memory, synth, control plane, SRS) do not depend on it.