ruview-advanced-sensing 精选

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.

编码 Claude Code Codex CLI MCP 客户端 MIT 9.8 万

在 GitHub 打开

安装方式

cp -r plugins/ruview/skills/ruview-advanced-sensing ~/.claude/skills/ruview-advanced-sensing

把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同，Claude Code 默认是 ~/.claude/skills/

整仓一次性获取：git clone --depth 1 https://github.com/ruvnet/RuView.git

依赖与权限

无需 API Key
无需联网
依赖外部命令：node python cargo
以上为按正文与 frontmatter 自动推断的信号，仅供参考；安装前建议先阅读原文。

allowed-tools: Bash Read Write Edit Glob Grep

SKILL.md 正文

来源 ruvnet/RuView@a71634a · 许可 MIT · 内容未修改

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

Host-side helpers to explore the geometry before deploying: node scripts/mesh-graph-transformer.js, node scripts/passive-radar.js, node scripts/deep-scan.js.

Persistent field model (ADR-030)

field_model.rs builds an SVD eigenstructure of the room and stores it (RVF, ideally on a Cognitum Seed). New CSI frames are projected against it; the residual is the perturbation. Lets you ask "what's different from the empty-room baseline?" and survive restarts.

RF tomography

tomography.rs reconstructs a voxel occupancy grid from the multistatic link set via an ISTA L1 solver (sparse — most voxels are empty). Use with cross-viewpoint geometry for through-wall volumetric imaging. RuVector solver crates back the sparse interpolation (114→56 subcarriers).

Sensing-first RF mode & adaptive mesh kernel

ADR-031 (RuView sensing-first RF mode), ADR-081 (adaptive CSI mesh firmware kernel), ADR-083 (per-cluster π compute hop), ADR-095/096 (on-ESP32 temporal modeling with sparse GQA attention — runs the temporal head on-device).

Security (ADR-032 — multistatic mesh hardening)

Using neighbours' APs as illuminators and pooling links across a mesh expands the attack surface. Mitigations:

adversarial.rs rejects physically impossible signals and cross-checks multi-link consistency.
coherence_gate.rs quarantines low-coherence / suspicious links (Reject / Recalibrate).
Ed25519 witness chain (ADR-028) attests every measurement.
Run a security review when touching anything on the hardware/network boundary (see ruview-verify and docs/security-audit-wasm-edge-vendor.md).

Validate advanced changes

cd v2 && cargo test --workspace --no-default-features      # incl. ruvsense + viewpoint tests
cargo test -p wifi-densepose-signal --no-default-features
cargo test -p wifi-densepose-ruvector --no-default-features
cd .. && python archive/v1/data/proof/verify.py

Reference

ADRs: 014 (SOTA signal processing), 029 (multistatic mode), 030 (persistent field model), 031 (sensing-first RF), 032 (mesh security hardening), 081/083/095/096
v2/crates/wifi-densepose-signal/src/ruvsense/ · v2/crates/wifi-densepose-ruvector/src/viewpoint/
docs/research/, docs/security-audit-wasm-edge-vendor.md