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ESPectre (Francesco Pace) — Technique Reference

Source: Pace's Part 2 (Dec 2025) + francescopace/espectre (GPLv3). Living checklist of techniques + RuView adoption status; update when items move.

1. Gain Lock (AGC + FFT scale)

The ESP32 PHY applies automatic gain control per packet. For normal WiFi reception that keeps decoding optimal; for CSI sensing it manifests as a 20-30 % slow drift in amplitude even in an empty room, masking real body modulation. Two undocumented PHY routines freeze the gain:

extern void phy_fft_scale_force(bool force_en, int8_t force_value);
extern void phy_force_rx_gain(int force_en, int force_value);

Recipe:

After WiFi association, collect AGC and FFT gain values from each CSI packet.
At packet 300 (~3 s at 100 pps), take the median of each (more robust than mean against outliers).
Call the two PHY routines with the medians to lock the radio.
Safety branch: if median AGC < 30, skip the lock — forcing low gain freezes the RX path. Sensor must be moved further from AP.

Supported targets: ESP32-S3, ESP32-C3, ESP32-C5, ESP32-C6. Older parts have no access to these PHY hooks.

RuView status — DONE. ADR-100 (commit 8aef8206). Implemented in firmware/esp32-csi-node/main/csi_collector.c as rv_gain_lock_process. Boot log on both sensors: gain-lock APPLIED: AGC=42/44, FFT=-31/-42 (median of 300 packets). Empty-room CV dropped from ~10 % (full broadband) to 3-4 % after NBVI also kicked in.

2. NBVI — Normalized Baseline Variability Index

Per-subcarrier score that picks the K most useful subcarriers automatically.

NBVI(k) = α · (σ_k / μ_k²) + (1 - α) · (σ_k / μ_k),    α = 0.5

σ_k / μ_k² penalises weak subcarriers (low μ → high score → bad).
σ_k / μ_k is the standard coefficient of variation; rewards stability.
α = 0.5 balances; pure σ/μ² picks stable-but-quiet bins, pure σ/μ picks loud-but-noisy bins.
Amplitude-only (no phase) — phase has Temporal Phase Rotation artefacts that need extra calibration; amplitude is calibration- free.

Four-step pipeline at boot:

Step	What	Detail
1	Find quiet moments	Slide a window across the calibration buffer, pick the windows with the lowest aggregate variance via percentile detection. Tolerates someone walking through during boot.
2	Dead-zone gate	Drop any subcarrier with mean amplitude below the 25th percentile across all subcarriers. Guard tones + null bins are excluded so they don't "win" σ/μ² → ∞.
3	Rank + validate	Sort by NBVI ascending. Run the motion detector on each candidate config, measure false-positive rate, take the config with the lowest FP.
4	Pick winners	Top-K by lowest NBVI (typically K = 12 for HT20).

Memory: O(N) running with on-the-fly mean/variance, ≈ 256 B for 64 subcarriers. Time: O(N · L) per recompute, ms on a $10 device.

RuView status — DONE (all 4 NBVI steps). Server-side: ADR-102 (2f12a223, f4119924) covers Steps 1+2+4; ADR-104 D4 (6212b17e) closes Step 3 (K ∈ {6,8,10,12,16,20} sweep, smallest-FP wins). FW- side boot freeze remains intentionally absent — server-side rolling refresh adapts to slow channel drift (ADR-102 D6).

Empirically on the operator's deployment NBVI alone gave a 1.5-2× CV reduction:

	Full 56 subc	NBVI top-12
node 1 idle CV	5.0 %	3.1 %
node 2 idle CV	7.0 %	3.9 %

3. Baseline-variance threshold normalization

Pace's third problem was that threshold = 1.0 meant different things on different devices. Fix:

if baseline_variance > 0.25:
    scale = 0.25 / baseline_variance
else:
    scale = 1.0

Reference 0.25 is what a quiet room typically measures during NBVI calibration. Apply the scale to the live motion score, so the user- facing threshold (= 1.0) is universal across rooms.

RuView status — DONE. ADR-103 D3 (commit 2f4b2d53). amp_node_level and amp_classify_from_latest divide live CV by baseline_cv loaded from data/baseline.json and gate at universal 3× (moving) / 6× (active). Falls back to absolute gates 0.10 / 0.22 when no calibration loaded — backwards compatible.

4. Two-phase boot calibration

PHASE 1: GAIN LOCK (3 s, 300 packets)
  Collect AGC/FFT → median → lock.
PHASE 2: NBVI CALIBRATION (7 s, 700 packets)
  With gain locked, rank subcarriers → pick top-K.
Total ≈ 10 s. Room must be mostly quiet during this window.

RuView status — SPLIT. Phase 1 is in FW (ADR-100). Phase 2 lives in the server as a rolling refresh, not a boot-time fix-point. See NBVI section above for the implications.

5. Persisted baseline / device threshold

After NBVI calibration, ESPectre writes the AGC/FFT lock values, the chosen subcarrier set, the baseline variance, and the threshold into NVS so reboots don't need re-calibration.

RuView status — DONE. Two-layer persistence:

Server side (ADR-103, commits f4119924, 2f4b2d53): data/baseline.json keeps per-node full-broadband mean/p95/CV + per-subcarrier means, loaded on server boot via load_baseline_file.
FW side (ADR-108, commit 3779bb76): gain-lock AGC + FFT saved to NVS namespace csi_cfg keys gl_agc/gl_fft after the first calibration; subsequent boots restore instantly (skip the 300-packet sampler). NBVI selection is intentionally server- side rolling, not persisted — design choice, not a gap.

6. Interactive Web Serial game (`espectre.dev/game`)

Browser ↔ ESP32 over USB Web Serial API. Shows live motion as a bar, lets user tune threshold while playing a reaction game. Settings persist via NVS.

RuView status — NOT DONE. Closest analogue is our raw.html calibration console (per-node bars + RSSI trace), but it's read-only.

7. Native Home Assistant integration via ESPHome

Sensor exposes occupancy/motion entities directly to HA.

RuView status — NOT DONE. No HA integration path. Could be added via MQTT or a custom ESPHome component.

8. Test suite

Pace ships 500+ unit tests, 90 % coverage, validated against a fixed 2000-packet capture (1000 idle + 1000 motion). CI runs PlatformIO, pytest, ESPHome build, Codecov on every push.

RuView status — PARTIAL. Agent added 2 regression tests for the binary CSI frame parser (csi.rs:751); no regression set captured for the amplitude classifier or NBVI.

Comparison summary (what RuView has, doesn't have, has differently)

Item	Pace / ESPectre	RuView
Gain lock	FW, 300 pkt median, AGC+FFT, AGC<30 skip	✅ ADR-100
NBVI formula α=0.5, top-12, dead-zone gate	✅	✅ ADR-102
Quiet-window finder (Step 1)	✅	✅ ADR-102 v2
FP-rate validation (Step 3)	✅	❌ raw ranking
Boot-time NBVI freeze	FW, ~7 s post-lock	❌ server-side rolling
Baseline variance normalization (universal threshold)	✅	✅ ADR-103 D3
Persisted baseline to disk	NVS	✅ ADR-103 D1 (`data/baseline.json`)
NVS persistence of FW calibration	✅	❌ fresh each FW boot
Calibration UI	Web Serial game	❌ read-only `raw.html`
HA / ESPHome integration	✅	❌ none
Test suite	500+ tests, 90 % cov	❌ 2 parser tests
Phase / amplitude	amplitude only	✅ same

Open items (full gap-by-section: `espectre-gap-analysis.md`)

REST POST /api/v1/baseline/calibrate — drives the recording script from a button in raw.html instead of CLI. ~30 min.
FP-rate validation of NBVI pick — defense against the top-12 accidentally overlapping a noise source. ~1 h.
Per-subcarrier baseline comparison (ADR-104 draft) — uses the already-saved per_subcarrier_mean in baseline.json for L2 distance instead of broadband mean ratio. Better off-axis presence sensing. ~1 h.
Auto-recalibrate on long quiet periods — if classifier sees absent with low variance for 30 min, refresh baseline in background. Eliminates manual script step entirely. ~1 h.
FW-side NBVI boot-freeze + NVS persistence — full reproducibility, sub-second post-boot ready. Trade-off: doesn't adapt to room changes. ~2 h.
HA / ESPHome integration — sensor as HA entity. ~1 day.
Test suite vs fixed 2 000-packet replay — regression protection for the classifier + NBVI. ~1 day.
Web Serial calibration game — nice-to-have. ~1 day.

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