mirror of
https://github.com/ruvnet/RuView
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d781f20e1a
New standalone leaf crate implementing the synthetic-aperture-radar reconstruction primitive a handheld through-wall RF imaging device would need: a stepped-frequency multi-position complex forward measurement simulator, delay-and-sum backprojection reconstruction, point-cloud extraction, and closed-form range/cross-range resolution + antenna-pose coherence-budget formulas checked against the reconstruction's actual behavior in tests/physics_validation.rs. Motivated by comparing this repo against Applied Electrodynamics' "WaveSight" launch. Scoped explicitly below ADR-278's RISE/DiffRadar/ GeRaF reproduction gates: this is the bare measurement-model + backprojection primitive, not a reproduction of any published system or a claim about real hardware capability. Every number is SYNTHETIC/L0 (ADR-282) -- no wideband RF hardware backs this crate. 24 tests (21 unit + 3 integration), 0 failed, clippy-clean. Adds a tutorial walkthrough and MEASURED backprojection benchmark numbers.
43 lines
1.6 KiB
TOML
43 lines
1.6 KiB
TOML
[package]
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name = "wifi-densepose-sar"
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description = "Coherent wideband RF tomography research crate (ADR-283): synthetic stepped-frequency multi-position measurement simulation + delay-and-sum backprojection reconstruction. SYNTHETIC/L0 only -- no wideband RF hardware backs this crate."
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version.workspace = true
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edition.workspace = true
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authors.workspace = true
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license.workspace = true
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repository.workspace = true
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documentation.workspace = true
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keywords = ["radar", "sar", "backprojection", "rf-tomography", "simulation"]
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categories = ["science", "simulation"]
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readme = "README.md"
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# `wifi-densepose-sar` is a standalone leaf crate (the nvsim / ruview-unified
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# pattern): pure-Rust math, deterministic ChaCha20 randomness (same seed =>
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# byte-identical output on every machine), zero coupling to any hardware
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# ingestion path. It has NO internal RuView dependency -- see the crate-level
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# doc comment in `src/lib.rs` for why (ADR-283 §2): this validates the
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# reconstruction *algorithm* against synthetic ground truth before any
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# question of wiring it into `ruview-unified`'s `FmcwRadarCube` adapter or
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# `GaussianMap` is in scope.
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[dependencies]
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num-complex = { workspace = true }
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thiserror = { workspace = true }
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serde = { workspace = true, features = ["derive"] }
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rand = { version = "0.8", default-features = false }
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rand_chacha = { version = "0.3", default-features = false }
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rayon = "1.10"
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[dev-dependencies]
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criterion = { workspace = true }
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[[bench]]
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name = "backprojection_bench"
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harness = false
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[lints.rust]
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unsafe_code = "forbid"
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missing_docs = "warn"
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[lints.clippy]
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all = "warn"
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