wifi-densepose/v2/crates/wifi-densepose-signal
ruv be068748b3 fix(signal): revive dead CIR coherence gate + NaN bypass + window div0 (ADR-154 M0)
Milestone-0 correctness/security fixes for the beyond-SOTA signal/DSP sweep.
Every fix ships with a committed regression test (proof, not adjectives).

CRITICAL — ADR-134 CIR coherence gate was DEAD in production
  MultistaticFuser fuses canonical-56 frames (hardware_norm.rs resamples every
  chipset onto a 56-tone grid), but the gate was wired to CirConfig::ht20()
  which expects 64/52. Every estimate() returned SubcarrierMismatch and
  cir_gate_coherence silently fell back to freq-domain coherence — use_cir_gate
  was indistinguishable from false. Fixes:
   - new CirConfig::canonical56() (64-bin HT20 framing, 56 active tones, 168 taps)
   - new MultistaticFuser::with_cir_canonical56() (correct default); ht20 kept,
     now doc-warned
   - active_indices() handles (64,56) + length-matched fallback (no silent
     fall-through to the 52-index slice)
   - SubcarrierMismatch in the gate now debug_assert!s loudly (config error can
     no longer hide as a graceful degrade)
   - cir_estimate_first() exposes the Ok/Err verdict for tests
  PROOF (ruvsense::multistatic::tests): ht20 → 8/8 Err (dead); canonical56 →
  8/8 Ok (alive); coherence(gate on) != coherence(gate off).

CRITICAL — adversarial.rs NaN/inf detector bypass
  One non-finite link energy bypassed the whole detector (every `e>thresh`
  false on NaN; score clamp returns NaN). A non-finite input is itself the
  strongest spoof — now short-circuits to a definite anomaly (score 1.0,
  affected link reported) and does not poison the temporal-continuity state.
  PROOF: nan_link_energy_flags_anomaly, inf_link_energy_flags_anomaly.

CORRECTNESS — divide-by-(n-1) window trio
  csi_processor hamming_window (n=0 usize underflow, n=1 div0), bvp Hann,
  spectrogram make_window all guarded for n<=1 (empty / constant-1.0 window).
  Python deterministic proof still PASS, same pipeline hash (reference uses n>=2).
  PROOF: *_degenerate_sizes / *_size_one_is_finite / make_window_size_0_and_1.

CLARITY — calibration.rs subtract_in_place
  Removed the vacuous `if active_input {ki} else {ki}` branch that implied a
  full-FFT->bin remap that never existed; documented the sequential
  active-index convention (matches sibling extract_first_stream). No behavior
  change.

Tests: cargo test -p wifi-densepose-signal --no-default-features (+--features cir)
green; full workspace green; verify.py VERDICT: PASS.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-06-11 19:20:37 -04:00
..
benches Beyond-SOTA engine/signal/train improvements: mesh partition guard, FFT CIR solver, canonical frame decoder, falsifiable occupancy benchmark, governed streaming, adapter provenance (#1018) 2026-06-11 16:08:54 -04:00
src fix(signal): revive dead CIR coherence gate + NaN bypass + window div0 (ADR-154 M0) 2026-06-11 19:20:37 -04:00
tests fix(signal/cir): un-ignore end-to-end CIR pipeline test — ADR-134 P2 fully resolved 2026-05-31 06:27:50 -04:00
Cargo.toml release: version bumps for crates.io publish (streaming-engine cascade) 2026-05-29 09:26:38 -04:00
README.md chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00

README.md

wifi-densepose-signal

Crates.io Documentation License

State-of-the-art WiFi CSI signal processing for human pose estimation.

Overview

wifi-densepose-signal implements six peer-reviewed signal processing algorithms that extract human motion features from raw WiFi Channel State Information (CSI). Each algorithm is traced back to its original publication and integrated with the ruvector family of crates for high-performance graph and attention operations.

Algorithms

Algorithm Module Reference
Conjugate Multiplication csi_ratio SpotFi, SIGCOMM 2015
Hampel Filter hampel WiGest, 2015
Fresnel Zone Model fresnel FarSense, MobiCom 2019
CSI Spectrogram spectrogram Common in WiFi sensing literature since 2018
Subcarrier Selection subcarrier_selection WiDance, MobiCom 2017
Body Velocity Profile (BVP) bvp Widar 3.0, MobiSys 2019

Features

  • CSI preprocessing -- Noise removal, windowing, normalization via CsiProcessor.
  • Phase sanitization -- Unwrapping, outlier removal, and smoothing via PhaseSanitizer.
  • Feature extraction -- Amplitude, phase, correlation, Doppler, and PSD features.
  • Motion detection -- Human presence detection with confidence scoring via MotionDetector.
  • ruvector integration -- Graph min-cut (person matching), attention mechanisms (antenna and spatial attention), and sparse solvers (subcarrier interpolation).

Quick Start

use wifi_densepose_signal::{
    CsiProcessor, CsiProcessorConfig,
    PhaseSanitizer, PhaseSanitizerConfig,
    MotionDetector,
};

// Configure and create a CSI processor
let config = CsiProcessorConfig::builder()
    .sampling_rate(1000.0)
    .window_size(256)
    .overlap(0.5)
    .noise_threshold(-30.0)
    .build();

let processor = CsiProcessor::new(config);

Architecture

wifi-densepose-signal/src/
  lib.rs                 -- Re-exports, SignalError, prelude
  bvp.rs                 -- Body Velocity Profile (Widar 3.0)
  csi_processor.rs       -- Core preprocessing pipeline
  csi_ratio.rs           -- Conjugate multiplication (SpotFi)
  features.rs            -- Amplitude/phase/Doppler/PSD feature extraction
  fresnel.rs             -- Fresnel zone diffraction model
  hampel.rs              -- Hampel outlier filter
  motion.rs              -- Motion and human presence detection
  phase_sanitizer.rs     -- Phase unwrapping and sanitization
  spectrogram.rs         -- Time-frequency CSI spectrograms
  subcarrier_selection.rs -- Variance-based subcarrier selection
Crate Role
wifi-densepose-core Foundation types and traits
ruvector-mincut Graph min-cut for person matching
ruvector-attn-mincut Attention-weighted min-cut
ruvector-attention Spatial attention for CSI
ruvector-solver Sparse interpolation solver

License

MIT OR Apache-2.0