# Advanced RuView Sensing

Runs multi-node sensing, RF tomography and drift analysis for research RuView setups.

- Repository: https://github.com/ruvnet/RuView (101983 stars)
- Category: Data and ML
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add ruvnet/RuView --skill ruview-advanced-sensing -g -a claude-code -y`
Codex: `npx skills add ruvnet/RuView --skill ruview-advanced-sensing -g -a codex -y`
Cursor: `npx skills add ruvnet/RuView --skill ruview-advanced-sensing -g -a cursor -y`
Gemini CLI: `npx skills add ruvnet/RuView --skill ruview-advanced-sensing -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add ruvnet/RuView`

## Description

Advanced RuView capabilities, RuvSense multistatic sensing (attention-weighted fusion, geometric diversity, persistent field model), cross-viewpoint fusion across multiple nodes, RF tomography (ISTA L1 solver, voxel grids), longitudinal biomechanics drift, pre-movement intention signals, adversarial signal detection, and multistatic mesh security hardening. Use for research-grade or multi-node deployments.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# RuView Advanced Sensing

The deep end: multistatic mesh, tomography, persistent field models, and the security model that protects them. Most of this lives in `wifi-densepose-signal/src/ruvsense/` (14 modules) and `wifi-densepose-ruvector/src/viewpoint/` (5 modules).

## RuvSense multistatic mode (ADR-029)

Treat every WiFi link in range, including neighbours' APs, as a bistatic radar pair, then fuse them.

| Module (`signal/src/ruvsense/`) | Purpose |
|--------------------------------|---------|
| `multiband.rs` | Multi-band CSI frame fusion, cross-channel coherence |
| `phase_align.rs` | Iterative LO phase-offset estimation, circular mean |
| `multistatic.rs` | Attention-weighted fusion, geometric diversity |
| `coherence.rs` / `coherence_gate.rs` | Z-score coherence scoring; Accept / PredictOnly / Reject / Recalibrate gate decisions |
| `pose_tracker.rs` | 17-keypoint Kalman tracker with AETHER re-ID embeddings |
| `field_model.rs` | SVD room eigenstructure, perturbation extraction |
| `tomography.rs` | RF tomography, ISTA L1 solver, voxel grid |
| `longitudinal.rs` | Welford stats, biomechanics drift detection |
| `intention.rs` | Pre-movement lead signals (200, 500 ms ahead) |
| `cross_room.rs` | Environment fingerprinting, transition graph |
| `gesture.rs` | DTW template-matching gesture classifier |
| `adversarial.rs` | Physically-impossible-signal detection, multi-link consistency |

## Cross-viewpoint fusion (ADR-016 viewpoint module)

Combine 2+ nodes geometrically, more nodes, more independent looks, tighter localization.

| Module (`ruvector/src/viewpoint/`) | Purpose |
|------------------------------------|---------|
| `attention.rs` | CrossViewpointAttention, GeometricBias, softmax with `G_bias` |
| `geometry.rs` | GeometricDiversityIndex, Cramér, Rao bounds, Fisher Information |
| `coherence.rs` | Phase-phasor coherence, hysteresis gate |
| `fusion.rs` | MultistaticArray aggregate root, domain events |

The rest: https://github.com/ruvnet/RuView/blob/HEAD/plugins/ruview/skills/ruview-advanced-sensing/SKILL.md