wifi-densepose/v2/crates/wifi-densepose-signal
ruv a27ee6f6cd fix(csi-ingest): real HE20 CSI no longer dropped or replaced with simulated data (#1009, #1004)
Two ingest bugs caused real ESP32-C6 HE20 CSI to be silently discarded or
never received — the "real data silently lost" failure class. Each fix is
pinned by a test that fails on the old code.

#1009 §1b — HE20 baseline recorder trimmed 256->242 bins by sequential index.
ESP-IDF v5.5.2 delivers all 256 FFT bins for an HE20 frame, but
CalibrationConfig::he20() carried num_active: 242, so the recorder (no HE20
tone map — extract_first_stream takes the first num_active columns
sequentially) kept bins 0..242 = the lower guard band + DC, NOT the 242 active
tones, silently corrupting the empty-room baseline. Now num_active: 256 records
every delivered bin, aligned 1:1 with the live deviation() path. The exact-242
tone map stays only in cir.rs (HE20_ACTIVE), where the Phi sensing matrix needs
it. HE20 synthetic/bench fixtures updated to feed 256-bin frames.

#1009 §1a/§1c — u8->u16 n_subcarriers truncation, regression-pinned.
The ADR-018 wire format carries n_subcarriers as u16 LE at bytes 6-7; a 256-bin
HE20 frame (byte6=0x00) read as one byte decodes to 0 subcarriers -> every
frame skipped. The CLI parser and the sensing-server parse_esp32_frame were
already corrected to u16 under #1005/ADR-110; added regression tests that fail
on the old single-byte read so the truncation cannot silently return.

#1004 — --source auto latched on simulate forever, never binding UDP :5005.
A one-shot boot probe resolved the source once; with no CSI flowing at boot
(the normal firmware/server startup race) it served simulated poses for the
whole process and ignored real CSI arriving seconds later (the prior #937 fix
hard-exited instead — equally wrong). New plan_source() state machine: in auto
mode ALWAYS bind the UDP receiver and serve simulated only until the first real
frame, then udp_receiver_task promotes source -> esp32 (mirroring the existing
esp32 -> esp32:offline reversion). simulated_data_task self-suspends once
promoted. Explicit --source simulated stays a hard, UDP-free offline override.

Validation: 3-crate tests 1118 passed / 0 failed; workspace 3166 passed /
0 failed; Python proof VERDICT: PASS (bit-exact, unaffected). cir.rs untouched.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-06-12 16:37:55 -04:00
..
benches fix(csi-ingest): real HE20 CSI no longer dropped or replaced with simulated data (#1009, #1004) 2026-06-12 16:37:55 -04:00
src fix(csi-ingest): real HE20 CSI no longer dropped or replaced with simulated data (#1009, #1004) 2026-06-12 16:37:55 -04:00
tests fix(csi-ingest): real HE20 CSI no longer dropped or replaced with simulated data (#1009, #1004) 2026-06-12 16:37:55 -04:00
Cargo.toml release: bump 9 crates changed in the beyond-SOTA sweep for crates.io 2026-06-11 22:41:21 -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