feat: ADR-024 Contrastive CSI Embedding Model — all 7 phases (#52)
Full implementation of Project AETHER — Contrastive CSI Embedding Model. ## Phases Delivered 1. ProjectionHead (64→128→128) + L2 normalization 2. CsiAugmenter (5 physically-motivated augmentations) 3. InfoNCE contrastive loss + SimCLR pretraining 4. FingerprintIndex (4 index types: env, activity, temporal, person) 5. RVF SEG_EMBED (0x0C) + CLI integration 6. Cross-modal alignment (PoseEncoder + InfoNCE) 7. Deep RuVector: MicroLoRA, EWC++, drift detection, hard-negative mining, SEG_LORA ## Stats - 276 tests passing (191 lib + 51 bin + 16 rvf + 18 vitals) - 3,342 additions across 8 files - Zero unsafe/unwrap/panic/todo stubs - ~55KB INT8 model for ESP32 edge deployment Also fixes deprecated GitHub Actions (v3→v4) and adds feat/* branch CI triggers. Closes #50
This commit was merged in pull request #52.
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rUv
@@ -4,6 +4,12 @@ version.workspace = true
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edition.workspace = true
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description = "WiFi CSI signal processing for DensePose estimation"
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license.workspace = true
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authors = ["rUv <ruv@ruv.net>", "WiFi-DensePose Contributors"]
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repository.workspace = true
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documentation = "https://docs.rs/wifi-densepose-signal"
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keywords = ["wifi", "csi", "signal-processing", "densepose", "rust"]
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categories = ["science", "computer-vision"]
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readme = "README.md"
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[dependencies]
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# Core utilities
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@@ -27,7 +33,7 @@ ruvector-attention = { workspace = true }
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ruvector-solver = { workspace = true }
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# Internal
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wifi-densepose-core = { path = "../wifi-densepose-core" }
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wifi-densepose-core = { version = "0.1.0", path = "../wifi-densepose-core" }
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[dev-dependencies]
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criterion = { version = "0.5", features = ["html_reports"] }
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@@ -0,0 +1,86 @@
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# wifi-densepose-signal
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[](https://crates.io/crates/wifi-densepose-signal)
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[](https://docs.rs/wifi-densepose-signal)
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[](LICENSE)
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State-of-the-art WiFi CSI signal processing for human pose estimation.
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## Overview
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`wifi-densepose-signal` implements six peer-reviewed signal processing algorithms that extract
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human motion features from raw WiFi Channel State Information (CSI). Each algorithm is traced
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back to its original publication and integrated with the
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[ruvector](https://crates.io/crates/ruvector-mincut) family of crates for high-performance
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graph and attention operations.
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## Algorithms
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| Algorithm | Module | Reference |
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|-----------|--------|-----------|
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| Conjugate Multiplication | `csi_ratio` | SpotFi, SIGCOMM 2015 |
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| Hampel Filter | `hampel` | WiGest, 2015 |
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| Fresnel Zone Model | `fresnel` | FarSense, MobiCom 2019 |
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| CSI Spectrogram | `spectrogram` | Common in WiFi sensing literature since 2018 |
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| Subcarrier Selection | `subcarrier_selection` | WiDance, MobiCom 2017 |
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| Body Velocity Profile (BVP) | `bvp` | Widar 3.0, MobiSys 2019 |
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## Features
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- **CSI preprocessing** -- Noise removal, windowing, normalization via `CsiProcessor`.
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- **Phase sanitization** -- Unwrapping, outlier removal, and smoothing via `PhaseSanitizer`.
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- **Feature extraction** -- Amplitude, phase, correlation, Doppler, and PSD features.
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- **Motion detection** -- Human presence detection with confidence scoring via `MotionDetector`.
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- **ruvector integration** -- Graph min-cut (person matching), attention mechanisms (antenna and
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spatial attention), and sparse solvers (subcarrier interpolation).
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## Quick Start
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```rust
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use wifi_densepose_signal::{
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CsiProcessor, CsiProcessorConfig,
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PhaseSanitizer, PhaseSanitizerConfig,
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MotionDetector,
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};
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// Configure and create a CSI processor
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let config = CsiProcessorConfig::builder()
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.sampling_rate(1000.0)
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.window_size(256)
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.overlap(0.5)
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.noise_threshold(-30.0)
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.build();
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let processor = CsiProcessor::new(config);
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```
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## Architecture
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```text
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wifi-densepose-signal/src/
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lib.rs -- Re-exports, SignalError, prelude
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bvp.rs -- Body Velocity Profile (Widar 3.0)
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csi_processor.rs -- Core preprocessing pipeline
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csi_ratio.rs -- Conjugate multiplication (SpotFi)
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features.rs -- Amplitude/phase/Doppler/PSD feature extraction
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fresnel.rs -- Fresnel zone diffraction model
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hampel.rs -- Hampel outlier filter
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motion.rs -- Motion and human presence detection
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phase_sanitizer.rs -- Phase unwrapping and sanitization
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spectrogram.rs -- Time-frequency CSI spectrograms
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subcarrier_selection.rs -- Variance-based subcarrier selection
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```
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## Related Crates
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| Crate | Role |
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|-------|------|
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| [`wifi-densepose-core`](../wifi-densepose-core) | Foundation types and traits |
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| [`ruvector-mincut`](https://crates.io/crates/ruvector-mincut) | Graph min-cut for person matching |
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| [`ruvector-attn-mincut`](https://crates.io/crates/ruvector-attn-mincut) | Attention-weighted min-cut |
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| [`ruvector-attention`](https://crates.io/crates/ruvector-attention) | Spatial attention for CSI |
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| [`ruvector-solver`](https://crates.io/crates/ruvector-solver) | Sparse interpolation solver |
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## License
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MIT OR Apache-2.0
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